Patent Application
20060242562
The present invention relates to embedding an embedded interaction code (EIC) into a document. More particularly, the present invention relates to configuring an EIC font in accordance with intended parameters of an EIC document system.
Computer users are accustomed to using a mouse and keyboard as a way of interacting with a personal computer. While personal computers provide a number of advantages over written documents, most users continue to perform certain functions using printed paper. Some of these functions include reading and annotating written documents. In the case of annotations, the printed document assumes a greater significance because of the annotations placed on it by the user. One of the difficulties, however, with having a printed document with annotations is the later need to have the annotations entered back into the electronic form of the document. This requires the original user or another user to wade through the annotations and enter them into a personal computer. In some cases, a user will scan in the annotations and the original text, thereby creating a new document. These multiple steps make the interaction between the printed document and the electronic version of the document difficult to handle on a repeated basis. Further, scanned-in images are frequently non-modifiable. There may be no way to separate the annotations from the original text. This makes using the annotations difficult. Accordingly, an improved way of handling annotations is needed.
One technique of capturing handwritten information is by using a pen whose location may be determined during writing. One pen that provides this capability is the Anoto pen by Anoto Inc. This pen functions by using a camera to capture an image of paper encoded with a predefined pattern. An example of the image pattern is shown in
Aspects of the present invention provide solutions to at least one of the issues mentioned above, thereby enabling one to configure a maze pattern to locate a position or positions of the captured image on a viewed document. The viewed document may be on paper, LCD screen, or any other medium with the predefined pattern. Aspects of the present invention include configuring an embedded interaction code (EIC) font that encodes EIC data and orientates an EIC symbol.
With one aspect of the invention, an embedded interaction code (EIC) document system is configured in order to support a desired address space of an EIC array, a desired decoding performance, and a desired level of readability of an EIC document.
With another aspect of the invention, an EIC font is configured to include a plurality of data dots along an edge. An EIC pattern that includes EIC symbols are formed from the selected EIC font. An EIC symbol is generated using the EIC font by encoding information bits within the EIC symbol. In order to encode a desired number of data bits, data dots are marked to represent the encoded data bits.
With another aspect of the invention, a geometric shape is selected for an EIC font. The selection considers a number of dimensions and the order to a constituent m-array, which is associated with one of the dimensions.
With another aspect of the invention, an EIC font is configured with at least one clock dot to support segmenting EIC symbols that are captured by a pen camera.
With another aspect of the invention, an EIC font is configured with at least one parity dot. An EIC symbol is generated in which the at least one parity dot is marked to provide an indication of either even or odd parity.
With another aspect of the invention, an EIC font is configured with at least one orientation dot. The at least one orientation dot is not marked so that a captured image can be properly orientated.
With another aspect of the invention, an EIC symbol is extracted from a captured image using orientation dots contained in each EIC symbol.
These and other aspects of the present invention will become known through the following drawings and associated description.
The foregoing summary of the invention, as well as the following detailed description of preferred embodiments, is better understood when read in conjunction with the accompanying drawings, which are included by way of example, and not by way of limitation with regard to the claimed invention.
Aspects of the present invention relate to determining the location of a captured image in relation to a larger image. The location determination method and system described herein may be used in combination with a multi-function pen.
The following is separated by subheadings for the benefit of the reader. The subheadings include: terms, general-purpose computer, image capturing pen, encoding of array, decoding, error correction, location determination, and maze pattern analysis.
Terms
Pen—any writing implement that may or may not include the ability to store ink. In some examples, a stylus with no ink capability may be used as a pen in accordance with embodiments of the present invention.
Camera—an image capture system that captures an image from paper or any other medium.
General Purpose Computer
A basic input/output system 160 (BIOS), containing the basic routines that help to transfer information between elements within the computer 100, such as during start-up, is stored in the ROM 140. The computer 100 also includes a hard disk drive 170 for reading from and writing to a hard disk (not shown), a magnetic disk drive 180 for reading from or writing to a removable magnetic disk 190, and an optical disk drive 191 for reading from or writing to a removable optical disk 192 such as a CD ROM or other optical media. The hard disk drive 170, magnetic disk drive 180, and optical disk drive 191 are connected to the system bus 130 by a hard disk drive interface 192, a magnetic disk drive interface 193, and an optical disk drive interface 194, respectively. The drives and their associated computer-readable media provide nonvolatile storage of computer readable instructions, data structures, program modules and other data for the personal computer 100. It will be appreciated by those skilled in the art that other types of computer readable media that can store data that is accessible by a computer, such as magnetic cassettes, flash memory cards, digital video disks, Bernoulli cartridges, random access memories (RAMs), read only memories (ROMs), and the like, may also be used in the example operating environment.
A number of program modules can be stored on the hard disk drive 170, magnetic disk 190, optical disk 192, ROM 140 or RAM 150, including an operating system 195, one or more application programs 196, other program modules 197, and program data 198. A user can enter commands and information into the computer 100 through input devices such as a keyboard 101 and pointing device 102. Other input devices (not shown) may include a microphone, joystick, game pad, satellite dish, scanner or the like. These and other input devices are often connected to the processing unit 110 through a serial port interface 106 that is coupled to the system bus, but may be connected by other interfaces, such as a parallel port, game port or a universal serial bus (USB). Further still, these devices may be coupled directly to the system bus 130 via an appropriate interface (not shown). A monitor 107 or other type of display device is also connected to the system bus 130 via an interface, such as a video adapter 108. In addition to the monitor, personal computers typically include other peripheral output devices (not shown), such as speakers and printers. In a preferred embodiment, a pen digitizer 165 and accompanying pen or stylus 166 are provided in order to digitally capture freehand input. Although a direct connection between the pen digitizer 165 and the serial port is shown, in practice, the pen digitizer 165 may be coupled to the processing unit 110 directly, via a parallel port or other interface and the system bus 130 as known in the art. Furthermore, although the digitizer 165 is shown apart from the monitor 107, it is preferred that the usable input area of the digitizer 165 be co-extensive with the display area of the monitor 107. Further still, the digitizer 165 may be integrated in the monitor 107, or may exist as a separate device overlaying or otherwise appended to the monitor 107.
The computer 100 can operate in a networked environment using logical connections to one or more remote computers, such as a remote computer 109. The remote computer 109 can be a server, a router, a network PC, a peer device or other common network node, and typically includes many or all of the elements described above relative to the computer 100, although only a memory storage device 111 has been illustrated in
When used in a LAN networking environment, the computer 100 is connected to the local network 112 through a network interface or adapter 114. When used in a WAN networking environment, the personal computer 100 typically includes a modem 115 or other means for establishing a communications over the wide area network 113, such as the Internet. The modem 115, which may be internal or external, is connected to the system bus 130 via the serial port interface 106. In a networked environment, program modules depicted relative to the personal computer 100, or portions thereof, may be stored in the remote memory storage device.
It will be appreciated that the network connections shown are illustrative and other techniques for establishing a communications link between the computers can be used. The existence of any of various well-known protocols such as TCP/IP, Ethernet, FTP, HTTP, Bluetooth, IEEE 802.11x and the like is presumed, and the system can be operated in a client-server configuration to permit a user to retrieve web pages from a web-based server. Any of various conventional web browsers can be used to display and manipulate data on web pages.
Image Capturing Pen
Aspects of the present invention include placing an encoded data stream in a displayed form that represents the encoded data stream. (For example, as will be discussed with
This determination of the location of a captured image may be used to determine the location of a user's interaction with the paper, medium, or display screen. In some aspects of the present invention, the pen may be an ink pen writing on paper. In other aspects, the pen may be a stylus with the user writing on the surface of a computer display. Any interaction may be provided back to the system with knowledge of the encoded image on the document or supporting the document displayed on the computer screen. By repeatedly capturing images with a camera in the pen or stylus as the pen or stylus traverses a document, the system can track movement of the stylus being controlled by the user. The displayed or printed image may be a watermark associated with the blank or content-rich paper or may be a watermark associated with a displayed image or a fixed coding overlying a screen or built into a screen.
The images captured by camera 203 may be defined as a sequence of image frames {Ii}, where Ii is captured by the pen 201 at sampling time ti. The sampling rate may be large or small, depending on system configuration and performance requirement. The size of the captured image frame may be large or small, depending on system configuration and performance requirement.
The image captured by camera 203 may be used directly by the processing system or may undergo pre-filtering. This pre-filtering may occur in pen 201 or may occur outside of pen 201 (for example, in a personal computer).
The image size of
The image sensor 211 may be large enough to capture the image 210. Alternatively, the image sensor 211 may be large enough to capture an image of the pen tip 202 at location 212. For reference, the image at location 212 is referred to as the virtual pen tip. It is noted that the virtual pen tip location with respect to image sensor 211 is fixed because of the constant relationship between the pen tip, the lens 208, and the image sensor 211.
The following transformation F→P transforms position coordinates in the image captured by camera to position coordinates in the real image on the paper:
Lpaper=FS→P(LSensor).
During writing, the pen tip and the paper are on the same plane. Accordingly, the transformation from the virtual pen tip to the real pen tip is also FS→P.
Lpentip=FS→P(Lvirtual-pentip).
The transformation FS→P may be estimated as an affine transform, which approximates FS→P as:
in which θx, θy, sx, and sy are the rotation and scale of two orientations of the pattern captured at location 204. Further, one can refine F′S→P by matching the captured image with the corresponding real image on paper. “Refine” means to get a more precise estimation of the transformation FS→P by a type of optimization algorithm referred to as a recursive method. The recursive method treats the matrix F′S→P as the initial value. The refined estimation describes the transformation between S and P more precisely.
Next, one can determine the location of virtual pen tip by calibration.
One places the pen tip 202 on a fixed location Lpentip on paper. Next, one tilts the pen, allowing the camera 203 to capture a series of images with different pen poses. For each image captured, one may obtain the transformation FS→P. From this transformation, one can obtain the location of the virtual pen tip Lvirtual-pentip:
Lvirtual-pentip=FP→S(Lpentip),
where Lpentip is initialized as (0, 0) and
FP→S=(FS→P)−1.
By averaging the Lvirtual-pentip obtained from each image, a location of the virtual pen tip Lvirtual-pentip may be determined. With Lvirtual-pentip) one can get a more accurate estimation of Lpentip. After several times of iteration, an accurate location of virtual pen tip Lvirtual-pentip may be determined.
The location of the virtual pen tip Lvitual-pentip is now known. One can also obtain the transformation FS→P from the images captured. Finally, one can use this information to determine the location of the real pen tip Lpentip:
Lpentip=FS→P(Lvirtual-pentip).
Encoding of Array
A two-dimensional array may be constructed by folding a one-dimensional sequence. Any portion of the two-dimensional array containing a large enough number of bits may be used to determine its location in the complete two-dimensional array. However, it may be necessary to determine the location from a captured image or a few captured images. So as to minimize the possibility of a captured image portion being associated with two or more locations in the two-dimensional array, a non-repeating sequence may be used to create the array. One property of a created sequence is that the sequence does not repeat over a length (or window) n. The following describes the creation of the one-dimensional sequence then the folding of the sequence into an array.
A sequence of numbers may be used as the starting point of the encoding system. For example, a sequence (also referred to as an m-sequence) may be represented as a q-element set in field Fq. Here, q=pn where n≧1 and p is a prime number. The sequence or m-sequence may be generated by a variety of different techniques including, but not limited to, polynomial division. Using polynomial division, the sequence may be defined as follows:
where Pn(x) is a primitive polynomial of degree n in field Fq[x] (having qn elements). Rl(x) is a nonzero polynomial of degree l (where l<n) in field Fq[x]. The sequence may be created using an iterative procedure with two steps: first, dividing the two polynomials (resulting in an element of field Fq) and, second, multiplying the remainder by x. The computation stops when the output begins to repeat. This process may be implemented using a linear feedback shift register as set forth in an article by Douglas W. Clark and Lih-Jyh Weng, “Maximal and Near-Maximal Shift Register Sequences: Efficient Event Counters and Easy Discrete Logarithms,” IEEE Transactions on Computers 43.5 (May 1994, pp 560-568). In this environment, a relationship is established between cyclical shifting of the sequence and polynomial Rl(x): changing Rl(x) only cyclically shifts the sequence and every cyclical shifting corresponds to a polynomial Rl(x). One of the properties of the resulting sequence is that, the sequence has a period of qn−1 and within a period, over a width (or length) n, any portion exists once and only once in the sequence. This is called the “window property”. Period qn−1 is also referred to as the length of the sequence and n as the order of the sequence.
The process described above is but one of a variety of processes that may be used to create a sequence with the window property.
The array (or m-array) that may be used to create the image (of which a portion may be captured by the camera) is an extension of the one-dimensional sequence or m-sequence. Let A be an array of period (m1, m2), namely A(k+m1,l)=A(k,l+m2)=A(k,l). When an n1×n2 window shifts through a period of A, all the nonzero n1×n2 matrices over Fq appear once and only once. This property is also referred to as a “window property” in that each window is unique. A widow may then be expressed as an array of period (m1, m2) (with m1 and m2 being the horizontal and vertical number of bits present in the array) and order (n1, n2).
A binary array (or m-array) may be constructed by folding the sequence. One approach is to obtain a sequence then fold it to a size of m1×m2 where the length of the array is L=m1×m2=2n−1. Alternatively, one may start with a predetermined size of the space that one wants to cover (for example, one sheet of paper, 30 sheets of paper or the size of a computer monitor), determine the area (m1×m2), then use the size to let L≧m1−m2, where L=2n−1.
A variety of different folding techniques may be used. For example,
To create the folding method as shown in
bkl=ai, where k=i mod(m1), l=i mod(m2), i=0, . . . , L−1. (1)
This folding approach may be alternatively expressed as laying the sequence on the diagonal of the array, then continuing from the opposite edge when an edge is reached.
Referring to
Referring back to
Here, more than one pixel or dot is used to represent a bit. Using a single pixel (or bit) to represent a bit is fragile. Dust, creases in paper, non-planar surfaces, and the like create difficulties in reading single bit representations of data units. However, it is appreciated that different approaches may be used to graphically represent the array on a surface. Some approaches are shown in
A bit stream is used to create the graphical pattern 403 of
Decoding
When a person writes with the pen of
For the determination of the orientation of the captured image relative to the whole encoded area, one may notice that not all the four conceivable corners shown in
Continuing to
Next, image 601 is analyzed to determine which corner is missing. The rotation amount o needed to rotate image 601 to an image ready for decoding 603 is shown as o=(θ plus a rotation amount {defined by which corner missing}). The rotation amount is shown by the equation in
is appreciated that the rotation angle θ may be applied before or after rotation of the image 601 to account for the missing corner. It is also appreciated that by considering noise in the captured image, all four types of corners may be present. We may count the number of corners of each type and choose the type that has the least number as the corner type that is missing.
Finally, the code in image 603 is read out and correlated with the original bit stream used to create image 403. The correlation may be performed in a number of ways. For example, it may be performed by a recursive approach in which a recovered bit stream is compared against all other bit stream fragments within the original bit stream. Second, a statistical analysis may be performed between the recovered bit stream and the original bit stream, for example, by using a Hamming distance between the two bit streams. It is appreciated that a variety of approaches may be used to determine the location of the recovered bit stream within the original bit stream.
As will be discussed, maze pattern analysis obtains recovered bits from image 603. Once one has the recovered bits, one needs to locate the captured image within the original array (for example, the one shown in
Let the sequence (or m-sequence) I correspond to the power series I(x)=1/Pn(x), where n is the order of the m-sequence, and the captured image contains K bits b=(b0 b1 b2 . . . bK-1)t of I, where K≧n and the superscript t represents a transpose of the matrix or vector. The location s of the K bits is just the number of cyclic shifts of I so that b0 is shifted to the beginning of the sequence. Then this shifted sequence R corresponds to the power series xs/Pn(x), or R=Ts(I), where T is the cyclic shift operator. We find this s indirectly. The polynomials modulo Pn(x) form a field. It is guaranteed that xs≡r0+r1x+ . . . rn-1xn-1 mod(Pn(x)). Therefore, we may find (r0, r1, . . . , rn-1) and then solve for s.
The relationship xs≡r0+r1x+ . . . rn-1xn-1 mod (Pn(x)) implies that R=r0+r1T(I)+ . . . +rn-1Tn-1(I). Written in a binary linear equation, it becomes:
R=rtA, (2)
where r=(r0 r1 r2 . . . rn-1)t, and A=(I T(I) . . . Tn-1(I)t which consists of the cyclic shifts of I from 0-shift to (n-1)-shift. Now only sparse K bits are available in R to solve r. Let the index differences between b1 and b0 in R be ki, i=1,2, . . . , k−1, then the 1st and (ki+1)-th elements of R, i=1,2, . . . , k−1, are exactly b0, b1, . . . , bk-1. By selecting the 1st and ( ki+1)-th columns of A, i=1,2, . . . , k−1, the following binary linear equation is formed:
bt=rtM, (3)
where M is an n x K sub-matrix of A.
If b is error-free, the solution of r may be expressed as:
rt={tilde over (b)}t{tilde over (M)}−1, (4)
where {tilde over (M)} is any non-degenerate n×n sub-matrix of M and {tilde over (b)} is the corresponding sub-vector of b.
With known r, we may use the Pohlig-Hellman-Silver algorithm as noted by Douglas W. Clark and Lih-Jyh Weng, “Maximal and Near-Maximal Shift Register Sequences: Efficient Event Counters and Easy Discrete Logorithms,” IEEE Transactions on Computers 43.5 (May 1994, pp 560-568) to find s so that xs≡r0+r1x+ . . . rn-1xn-1mod(Pn(x)).
As matrix A (with the size of n by L, where L=2n−1) may be huge, we should avoid storing the entire matrix A. In fact, as we have seen in the above process, given extracted bits with index difference ki, only the first and (ki+1)-th columns of A are relevant to the computation. Such choices of ki is quite limited, given the size of the captured image. Thus, only those columns that may be involved in computation need to saved. The total number of such columns is much smaller than L (where L=2n−1 is the length of the m-sequence).
Error Correction
If errors exist in b, then the solution of r becomes more complex. Traditional methods of decoding with error correction may not readily apply, because the matrix M associated with the captured bits may change from one captured image to another.
We adopt a stochastic approach. Assuming that the number of error bits in b, ne, is relatively small compared to K, then the probability of choosing correct n bits from the K bits of b and the corresponding sub-matrix {tilde over (M)} of M being non-degenerate is high.
When the n bits chosen are all correct, the Hamming distance between bt and rtM, or the number of error bits associated with r, should be minimal, where r is computed via equation (4). Repeating the process for several times, it is likely that the correct r that results in the minimal error bits can be identified.
If there is only one r that is associated with the minimum number of error bits, then it is regarded as the correct solution. Otherwise, if there is more than one r that is associated with the minimum number of error bits, the probability that ne exceeds the error correcting ability of the code generated by M is high and the decoding process fails. The system then may move on to process the next captured image. In another implementation, information about previous locations of the pen can be taken into consideration. That is, for each captured image, a destination area where the pen may be expected next can be identified. For example, if the user has not lifted the pen between two image captures by the camera, the location of the pen as determined by the second image capture should not be too far away from the first location. Each r that is associated with the minimum number of error bits can then be checked to see if the location s computed from r satisfies the local constraint, i.e., whether the location is within the destination area specified.
If the location s satisfies the local constraint, the X, Y positions of the extracted bits in the array are returned. If not, the decoding process fails.
In step 803, n independent column vectors are randomly selected from the matrix M and vector r is determined by solving equation (4). This process is performed Q times (for example, 100 times) in step 804. The determination of the number of loop times is discussed in the section Loop Times Calculation.
In step 805, r is sorted according to its associated number of error bits. The sorting can be done using a variety of sorting algorithms as known in the art. For example, a selection sorting algorithm may be used. The selection sorting algorithm is beneficial when the number Q is not large. However, if Q becomes large, other sorting algorithms (for example, a merge sort) that handle larger numbers of items more efficiently may be used.
The system then determines in step 806 whether error correction was performed successfully, by checking whether multiple r's are associated with the minimum number of error bits. If yes, an error is returned in step 809, indicating the decoding process failed. If not, the position s of the extracted bits in the sequence (or m-sequence) is calculated in step 807, for example, by using the Pohig-Hellman-Silver algorithm.
Next, the (X,Y) position in the array is calculated as: x=s mod m1 and y=s mod m2 and the results are returned in step 808.
Location Determination
In step 901, an image is received from a camera. Next, the received image may be optionally preprocessed in step 902 (as shown by the broken outline of step 902) to adjust the contrast between the light and dark pixels and the like.
Next, in step 903, the image is analyzed to determine the bit stream within it.
Next, in step 904, n bits are randomly selected from the bit stream for multiple times and the location of the received bit stream within the original sequence (or m-sequence) is determined.
Finally, once the location of the captured image is determined in step 904, the location of the pen tip may be determined in step 905.
Next, the received image is analyzed in step 1004 to determine the underlying grid lines. If grid lines are found in step 1005, then the code is extracted from the pattern in step 1006. The code is then decoded in step 1007 and the location of the pen tip is determined in step 1008. If no grid lines were found in step 1005, then an error is returned in step 1009.
Outline of Enhanced Decoding and Error Correction Algorithm
With an embodiment of the invention as shown in
Decode Once. Component 1251 include three parts.
Decoding with Smart Bit Selection. Component 1253 include four parts.
The embodiment of the invention utilizes a discreet strategy to select bits, adjusts the number of loop iterations, and determines the X,Y position (location coordinates) in accordance with a local constraint, which is provided to process 1200. With both components 1251 and 1253, steps 1205 and 1219 (“Decode Once”) utilize equation (4) to compute r.
Let b be decoded bits, that is:
{circumflex over (b)}′=rtM (5)
The difference between b and {circumflex over (b)} are the error bits associated with r.
If step 1207 detects error bits in b, component 1253 is executed in order to decode with error bits. Step 1217 selects another set of n bits (which differ by at least one bit from the n bits selected in step 1203) from extracted bits 1201. Steps 1221 and 1223 determine the number of iterations (loop times) that are necessary for decoding the extracted bits. Step 1225 determines the position of the captured array by testing which candidates obtained in step 1219 satisfy the local constraint. Steps 1217-1225 will be discussed in more details.
Smart Bit Selection
Step 1203 randomly selects n bits from extracted bits 1201 (having K bits), and solves for r1. Using equation (5), decoded bits can be calculated. Let I1={k ε{1,2, . . . , K}|bk={circumflex over (b)}k}, {overscore (I)}1={k ε{1,2, . . . , K}|bb≠{circumflex over (b)}k}, where {circumflex over (b)}k is the kth bit of {circumflex over (b)}, B1={bk|k εI1} and {overscore (B)}1{bk|k ε{overscore (I)}1}, that is, B1 are bits that the decoded results are the same as the original bits, and {overscore (B)}1 are bits that the decoded results are different from the original bits, I1 and {overscore (I)}1 are the corresponding indices of these bits. It is appreciated that the same r1 will be obtained when any n independent bits are selected from B1. Therefore, if the next n bits are not carefully chosen, it is possible that the selected bits are a subset of B1, thus resulting in the same r1 being obtained.
In order to avoid such a situation, step 1217 selects the next n bits according to the following procedure:
Loop Times Calculation
With the error correction component 1253, the number of required iterations (loop times) is adjusted after each loop. The loop times is determined by the expected error rate. The expected error rate pe in which not all the selected n bits are correct is:
where lt represents the loop times and is initialized by a constant, K is the number of extracted bits from the captured array, ne represents the minimum number of error bits incurred during the iteration of process 1200, n is the order of the m-array, and CKn is the number of combinations in which n bits are selected from K bits.
In the embodiment, we want pe to be less than e−5=0.0067. In combination with (6), we have:
Adjusting the loop times may significantly reduce the number of iterations of process 1253 that are required for error correction.
Determine X, Y Position with Local Constraint
In steps 1209 and 1225, the decoded position should be within the destination area. The destination area is an input to the algorithm, and it may be of various sizes and places or simply the whole m-array depending on different applications. Usually it can be predicted by the application. For example, if the previous position is determined, considering the writing speed, the destination area of the current pen tip should be close to the previous position. However, if the pen is lifted, then its next position can be anywhere. Therefore, in this case, the destination area should be the whole m-array. The correct X,Y position is determined by the following steps.
In step 1224 process 1200 selects ri whose corresponding number of error bits is less than:
where lt is the actual loop times and lr represents the Local Constraint Rate calculated by:
where L is the length of the m-array.
Step 1224 sorts ri in ascending order of the number of error bits. Steps 1225, 1211 and 1212 then finds the first ri in which the corresponding X,Y position is within the destination area. Steps 1225, 1211 and 1212 finally returns the X,Y position as the result (through step 1213), or an indication that the decoding procedure failed (through step 1215).
Illustrative Example of Enhanced Decoding and Error Correction Process
An illustrative example demonstrates process 1200 as performed by components 1251 and 1253. Suppose n=3, K=5, I=(I0 I1 . . . I6)t is the m-sequence of order n=3. Then
Also suppose that the extracted bits b=(b0 b1 b2 b3 b4)t, where K=5, are actually the sth, (s+1)th, (s+3)th, (s+4)th, and (s+6)th bits of the m-sequence (these numbers are actually modulus of the m-array length L=2n−1=23−1=7). Therefore
which consists of the 0th, 1st, 3rd, 4th, and 6th columns of A. The number s, which uniquely determines the X,Y position of b0 in the m-array, can be computed after solving r=(r0 r1 r2)t that are expected to fulfill bt=rtM. Due to possible error bits in b, bt=rtM may not be completely fulfilled.
Process 1200 utilizes the following procedure. Randomly select n=3 bits, say {tilde over (b)}1t=(b0 b1 b2), from b. Solving for r1:
{tilde over (b)}1t=r1t{tilde over (M)}1, (12)
where M1 consists of the 0th, 1st, and 2nd columns of M. (Note that {tilde over (M)}1 is an n×n matrix and r1t is a 1×n vector so that {tilde over (b)}1t is a 1×n vector of selected bits.)
Next, decoded bits are computed:
{circumflex over (b)}1t=r1tM, (13)
where M is an n×K matrix and r1t is a 1×n vector so that {circumflex over (b)}1t is a 1×K vector. If {circumflex over (b)}1 is identical to b, i.e., no error bits are detected, then step 1209 determines the X,Y position and step 1211 determines whether the decoded position is inside the destination area. If so, the decoding is successful, and step 1213 is performed. Otherwise, the decoding fails as indicated by step 1215. If {circumflex over (b)}1 is different from b, then error bits in b are detected and component 1253 is performed. Step 1217 determines the set B1, say {b0 b1 b2 b3}, where the decoded bits are the same as the original bits. Thus, {overscore (B)}1={b4} (corresponding to bit arrangement 1351 in
Step 1217 next chooses another n=3 bits from b. If the bits all belong to B1, say {b0 b2 b3}, then step 1219 will determine r1 again. In order to avoid such repetition, step 1217 may select, for example, one bit {b4} from {overscore (B)}1, and the remaining two bits {b0 b1} from By.
The selected three bits form {tilde over (b)}2t=(b0 b1 b4). Step 1219 solves for r2:
{tilde over (b)}2t=r2t{tilde over (M)}2, (14)
where {tilde over (M)}2 consists of the 0th, 1st, and 4th columns of M.
Step 1219 computes {circumflex over (b)}2tM=r2tM. Find the set B2, e.g., {b0 b1 b4}such that {circumflex over (b)}2 and b are the same. Then {overscore (B)}2={b2 b3} (corresponding to bit arrangement 1353 in
Because another iteration needs to be performed, step 1217 chooses another n=3 bits from b. The selected bits shall not all belong to either B1 or B2. So step 1217 may select, for example, one bit {b4} from {overscore (B)}1, one bit {b2} from {overscore (B)}2, and the remaining one bit {b0}.
The solution of r, bit selection, and loop times adjustment continues until we cannot select any new n=3 bits such that they do not all belong to any previous Bi's, or the maximum loop times It is reached.
Suppose that process 1200 calculates five ri (i=1,2,3,4,5), with the number of error bits corresponding to 1, 2, 4, 3, 2, respectively. (Actually, for this example, the number of error bits cannot exceed 2, but the illustrative example shows a larger number of error bits to illustrate the algorithm.) Step 1224 selects ri's, for example, r1,r2,r4,r5, whose corresponding numbers of error bits are less than Ne shown in (8).
Step 1224 sorts the selected vectors r1,r2,r4,r5 in ascending order of their error bit numbers: r1,r2,r5,r4. From the sorted candidate list, steps 1225, 1211 and 1212 find the first vector r, for example, r5, whose corresponding position is within the destination area. Step 1213 then outputs the corresponding position. If none of the positions is within the destination area, the decoding process fails as indicated by step 1215.
Embedding Method for Embedded Interaction Code Array
In order to determine the position of a digital pen on a document, information encoded in an embedded interaction code (EIC) is extracted from the document. The present invention defines and selects an optimal set of EIC fonts for visually representing the EIC symbols on different surfaces including printed documents. An EIC font refers to a specific size and visual design of an EIC symbol given the number of encoded bits. From a huge set of possible EIC fonts, only a small subset are suitable for practical use based on design considerations, including the efficiency to analyze a captured EIC pattern and segment the EIC symbols from the captured EIC pattern and the robustness of the EIC pattern over various scales, rotations and perspective distortions resulting from pen rotation and tilting.
X-y position information may be embedded in documents on flat surfaces. When an image capturing device moves on such surfaces, the device may track the position by reading the embedded data. The device may be a digital pen with a camera assembled near the pen tip. The surfaces may be blank paper, printed documents, whiteboard or LCD displays. For printed documents, embedding may be done by printing additional black dots (associated with EIC data) together with the document content, i.e. representing x-y position by using the special arrangement of additional black dots. Other technologies may be used to embed data in other surfaces.
When referring to “black dots,” a dot is marked. For example, ink may be applied on a region that is defined by a dot. With a document displayed on a video display device, a pixel or a group of pixels may be illuminated.
Metadata, such as document ID and other global or local information, may be embedded together with the x-y position to distinguish different surfaces or different functional areas in one surface. For example, one may print several documents, and embed a different document ID on the documents. If a digital pen is used to sketch or annotate on these documents, the pen knows both its position and the document ID which is associated with the document. Furthermore, the pen may switch among these documents freely to determine the position of the pen on the associated document.
An EIC symbol is the smallest unit for the visual representation of EIC array. An EIC symbol includes:
An EIC symbol may be classified by the number of encode bits, e.g., 1 bit EIC symbol, 2 bit EIC symbol, etc.
An EIC font refers to a specific size and visual design of an EIC symbol, given the number of encoded bits. One may select one of different EIC fonts for an EIC symbol with a specified number of bits. An EIC symbol is generated from the selected EIC font.
To represent an EIC array with K dimensions, a K×n bit EIC font may be used, where n is an integer, for example, 1, 2, or 3. Consequently n elements of an EIC array are represented in one EIC symbol.
EIC fonts may be identified by the EIC font (EF) notation:
There are numerous choices for EIC fonts that can be used to represent an EIC array with specified dimensions. First, to represent EIC array with K dimensions, an EIC font with K×n bits may be used, where n is any integer. Furthermore, one can design a great number of EIC fonts with specific number of bits. For example, EIC fonts “EF-square-1 bit-solid-12”, “EF-square-1 bit-dashed-12”, and “EF-square-1 bit-dot05-12” may be used to represent 1 bit. One can also design other fonts to represent 1 bit or any other number of bits. (The maximum number of encoded bits is limited by device limitations such as camera resolution and printer resolution.) However, among the huge number of possible EIC fonts, typically only a small subset is suitable for practical use. Some basic considerations are listed in the following discussion.
To decode the embedded x-y position and metadata from a captured EIC pattern (as captured by a camera in the pen), the data in different dimensions is embedded in a “decoupled” way. To achieve this, the number of bits encoded in an EIC font is a multiple of the EIC array dimension. When an EIC symbol is segmented, the bits of one or more complete elements are obtained, and the data in different dimensions can be easily separated. In contrast, this approach may not be efficient. If the data in the same element is represented in multiple symbols, extra efforts for data alignment are needed, i.e., one needs to determine what data in which EIC symbols belong to an element. In other words, for an EIC array with K dimensions, an EIC font with K×n bits may be used, i.e., n elements of EIC array are represented in one EIC symbol. For example, a one dimensional EIC array may use an m bit EIC font, where m is an integer. A two dimensional EIC array may use a 2×m bit EIC font.
Different surfaces may need different EIC fonts because the basic unit for representing information on different surfaces is different. For example, the basic unit of a printed document is a printed dot, whereas the basic unit for surfaces other than paper may not be printed dots. The invention supports different types of displays for displaying an EIC document. As previously discussed, embodiments of the invention present an EIC document in printed form. Other embodiments of the invention present an EIC document on a video display. In such cases, a dot may be a pixel or a group of pixels.
Also, one should consider user usability. For example, to work with a printed document, the EIC pattern should not be too dark to impede reading by a user.
An EIC font is designed as follows with the above considerations.
Simple Geometric Structure
To make EIC pattern (e.g., EIC patterns 2009, 2011, 2109, and 2111) appear homogeneous, the length of each edge of one EIC font unit is selected to be the same, i.e., using a rotational symmetrical structure. Therefore, one uses a square shape rather than a rectangle shape and an equilateral triangle rather than other triangle types. Since two adjacent symbols share the same edges and vertexes, one assigns the shared edge or vertex to the left and top symbols for convenience. For triangle and hexagon shapes, the two adjacent rows of an EIC symbol should have an offset to form the whole pattern, as shown in
Representation of Multiple Bits in One EIC Symbol
An EIC symbol (font) may represent multiple bits by utilizing multiple dimensions. Each dimension corresponds to an m-array that provides a corresponding bit steam. The bit streams are combined to obtain the EIC data. For example, eight dimensions may be supported by eight m-arrays, where eight bits are encoded in each EIC font. A “black dot” may be related to one or more bits, and thus to one or more m-arrays. For example, the black dots in EIC font EF-Square-1 bit-dot05-12 (shown in
There are several approaches for representing multiple bits in one EIC symbol:
1. Data can be represented by putting black dots in one of the edges of the selected geometric shape. For example, by using square shape, “1” or “0” may be represented by putting black dots on all positions of a vertical/horizontal edge of a symbol. To decrease the darkness, one may put black dots on a uniform portion (e.g., as one half or one third) of the positions of an edge. For example, the two EIC fonts that are shown in
2. Data can also be represented by putting one black dot in different positions as shown in
The difference of the data values of adjacent positions should be minimized as much as possible. With this approach, there is only one error bit if there is a small shift between estimated position of darkest dot and the real one. For example, one applies Gray coding (the difference between two adjacent Gray codes is just 1 bit).
3. Data may also be represented by putting or not putting a black dot in one position of an edge. For an EIC font with M edges and with J positions in each edge, M×J bits of information may be encoded. This approach enables more bits to be encoded in specified size of an EIC symbol than the previous approach. However, there are two disadvantages. First, to determine whether the bit is represented in one position, one needs to determine if the dot is black or not. It may be more difficult than to tell the relative darkness of several dots. Second, the formed EIC pattern may not be uniform. If a bit stream contains a continuous sequence of “0” or “1”, the pattern may be a continuous series of black dots or white dots, which does not appear uniform to the user.
4. A parity check bit may also be represented to detect the error bits from the extracted data under conditions when the quality of captured images is poor. For example, to represent K bits in one symbol, a parity check bit P may be represented as well. The value of P is equal to the binary summation of the K bits to be represented. When these K+1 bits are extracted, one can estimate if error bits occur among K bits by checking if the summation of extracted K bits is equal to the value of extracted parity check bit. The parity check can only detect an odd number of error bits. A parity check bit may not be necessary for an EIC font design if the quality of captured images is adequate.
Orientation Property
If an EIC font has no orientation property, one can enumerate all possible orientations and extract bits and decode position data and metadata for all possible orientations. Decoding the extracted bits for an incorrect orientation should fail with a large probability. However, the computing cost for determining the correct orientation by decoding may be significant relative to using an EIC font having an-orientation property.
The “orientation property” can be obtained by (a): always putting black dots in several non-rotational symmetrical positions of the symbol or (b): using non-rotational symmetrical positions on the edge to represent data, and keeping selected non-rotational symmetrical positions always white. Actually, approach (b) may be advantageous over approach (a) because the darkness of the whole EIC pattern is not increased. The following examples achieve an “orientation property” with approach (b).
As an example, with an EIC font denoted EF-square-2 bit-c-12, one can calculate the probability that the correct orientation property is selected. One assumes the distribution of “0” and “1” in EIC array as being uniform, i.e., the probability that any binary digit in the element of any position in an EIC array is equal to “0” is 50%, and consequently the probability of “1” is also 50%. This assumption is typically reasonable for an EIC array. Further, one assumes that there are 30 visible EIC symbols in one captured EIC pattern. One EIC symbol with a correct orientation cannot be distinguished from the EIC symbol rotated by 90 degrees in anti-clockwise under the condition that the dot in case 2605 corresponds to orientation dot (2641) being white, which has a probability of 50%. Therefore, the probability that the EIC pattern with 30 EIC symbols in the correct orientation cannot be distinguished from the EIC pattern rotated by 90 degrees in an anti-clockwise direction is (0.5)30=9×10−10, which is a very small value. The probability that the EIC pattern with 30 EIC symbols in the correct orientation cannot be distinguished from the EIC pattern rotated by 270 degrees in an anti-clockwise direction (corresponding to case 2609) is also 9×10−10. Similarly, the probability that the EIC pattern with 30 EIC symbols in correct orientation cannot be distinguished from the EIC pattern rotated by 180 degrees in an anti-clockwise direction (corresponding to case 2607) is (0.25)30=8×10−19, since the probability that both dot positions 2643 and 2645 are white is 0.25. Consequently, the probability that the EIC pattern with 30 EIC symbols in the correct orientation can be distinguished from the EIC pattern rotated by 90, 180 or 270 degrees is: (1−0.530)×(1−0.2530)×(1−0.530)=99.9999%.
For other shaped EIC symbols, one can design EIC fonts with an orientation property in a similar way.
Sample EIC Fonts
Additional EIC fonts may be designed in a similar way as with the previously discussed EIC fonts.
Process for Designing EIC Font
The address space of an EIC array is corresponds to the summation of the m-array order of each dimension. The address space is an important index of the capability of an EIC document system. A larger address space may generate a bigger area of EIC patterns (given the same EIC symbol size), thus covering more document pages.
To achieve a large system address space, one may use EIC array with multiple dimensions, and multiple bits EIC font. The m-array order is determined by step 4107. As previously discussed, each m-array corresponds to a dimension. Each bit encoded by an EIC font corresponds to a dimension. One reason for using a multiple dimensional EIC array is to reduce the algorithmic complexity of m-array decoding with error bits. The algorithmic complexity is proportional to m3, where m is m-array order. A very large m-array order results in the decoding time cost being very large. For example, for a 224-bit EIC document system, one can use an eight-dimensional EIC array with eight m-arrays of order 28. With the example, the complexity measure of decoding for the example is 8 times 283. If one uses a four-dimensional EIC array with four m-arrays of order 56, the complexity measure is 4 times 563, which is much larger than the first EIC configuration. The number of dimensions is determined by step 4109. Therefore, the exemplary embodiment uses the first EIC configuration, which corresponds to 8-bit EIC font 3601 (corresponding to EF-diamond-8 bit-a-14 EIC font as shown in
In the exemplary embodiment, the EIC document system is designed to obtain 224 usable (decodable) bits in a camera image. Other exemplary embodiments may be designed for a different number of bits per camera image using process 4100.
To insure that the captured EIC pattern images generated by a specific EIC array is decodable, a large enough camera array size and field of view (FOV) is required as determined by steps 4129, 4131, 4133, 4119, 4121, 4123, and 4135. The number of bits in the FOV determines the order of the m-array that can be decoded. For an m-array with the order of N, the number of bits in the FOV must be larger than N. For example, with an eight-dimensional EIC font, as discussed above, each m-array requires at least 28 bits per camera image. Consequently, the minimum total number of bits per camera image for decoding is 224 bits (28*8).
In order to ascertain that the EIC document system functions robustly, document occlusion should also be considered because document content printed by carbon ink may occlude the EIC pattern. For example, for an m-array with order 224, if one assumes 50% occlusion, then one typically designs a camera system that provides 448 visible bits in an area without occlusion.
EIC image processing and decoding should be efficient and effective. EIC font design should enable EIC image processing and decoding to overcome challenges posed by the application, namely, a document pen (e.g., a digital pen that works with printed documents). Design factors include:
A simple geometry structure and orientation property of an EIC font ensures the efficiency of EIC image processing. On the other hand, a multiple bit EIC font design improves the decoding efficiency greatly as previously discussed.
Process 4100 typically uses a square-shaped EIC font (e.g., EIC font 2001 shown in
Visual appearance of an EIC pattern is important from a usability point of view since one prints an EIC pattern with documents. An EIC pattern should be aesthetically pleasing and not degrade the reading experience. Typically, the legibleness (of EIC patterns at reading distance), evenness, and darkness affect subjective evaluation and preference of the EIC font. Typically, the less legible, the more even, and the lighter the EIC pattern, the better.
There may be different ways to print EIC patterns, for example invisible ink. With the advancement of printing technology, particularly with the introduction of cheaper invisible ink (invisible to the human eye but visible to pen camera), EIC patterns may be printed with the invisible ink on printed document or printed books. This may significantly increase the usability and utility of a digital pen.
To support EIC printing with a different DPI, one may maintain the size of EIC symbol. For example, if one prints an EIC font EF-8 bit-a-16 with a 600 DPI-printer, the physical size of a EIC symbol is 0.677 mm×0.677 mm (=16*25.4 mm/600). To print the EIC pattern with same size using a 1200 DPI-printer, one uses 2×2 black dots to simulate one black dot with 600 DPI-printer. Thus, the size of an EIC symbol is approximately the same with that printed with 600 DPI-printer.
As can be appreciated by one skilled in the art, a computer system with an associated computer-readable medium containing instructions for controlling the computer system can be utilized to implement the exemplary embodiments that are disclosed herein. The computer system may include at least one computer such as a microprocessor, digital signal processor, and associated peripheral electronic circuitry.
Although the invention has been defined using the appended claims, these claims are illustrative in that the invention is intended to include the elements and steps described herein in any combination or sub combination. Accordingly, there are any number of alternative combinations for defining the invention, which incorporate one or more elements from the specification, including the description, claims, and drawings, in various combinations or sub combinations. It will be apparent to those skilled in the relevant technology, in light of the present specification, that alternate combinations of aspects of the invention, either alone or in combination with one or more elements or steps defined herein, may be utilized as modifications or alterations of the invention or as part, of the invention. It may be intended that the written description of the invention contained herein covers all such modifications and alterations.
