The invention relates to a hardcopy-based computer user interface scheme for document processing applications and, more particularly, to a tag-based user interface scheme adapted to perform services with a hardcopy document dependent on user or service information stored as printed data on a tag associated with the document.
Many people are most comfortable dealing with documents in hardcopy format. In general, hardcopy documents are easier to read, handle, and store than documents kept in the digital domain. No special expertise or computer hardware is needed.
However, in general, manipulating documents in the digital domain is far easier. Text can be indexed, searched upon, reformatted, extracted, and otherwise changed. Stored documents can be easily duplicated, without loss of quality, and transmitted from person to person (for example, via e-mail). And significantly, all of this manipulation can be accomplished without using paper. Moreover, digital copiers and scanners are becoming far more prevalent in both office and home settings.
On the other hand, handling documents in the digital domain typically requires access to a computer system or network. If the user of the computer system does not have a baseline level of expertise or competence in using the system, then productivity can suffer. This consideration can be a serious impediment to the implementation of a “paperless office,” in which digital documents are the prevailing document type.
Accordingly, there is a need to be able to effectively manage documents in the digital domain, as well as to ease the transition from hardcopy documents to digital documents.
Previous attempts to facilitate handling digital documents have often used traditional user-interface paradigms. For example, when a hardcopy document is to be scanned and entered into a document repository, commands to that effect are first entered into a computer terminal or scanning device, which then performs the desired service with the document. A similar sequence of steps is performed when the hardcopy is to be scanned and faxed, scanned and e-mailed, scanned and recognized (via optical character recognition software), or any of numerous other possibilities. Although the entry of commands can be facilitated via user-friendly software or self-explanatory commands, these extra steps are still tedious and may still require a certain level of expertise. Moreover, the sequence of commands entered may be lost once the operation has been performed, and there is a potential for error even with experienced users.
Another possibility is to employ a cover sheet that includes a form for specifying commands. The cover sheet is filled out as the user desires (either by hand-writing commands or by marking check-boxes, for example), and the scanner interprets the commands on the cover sheet and processes the following document accordingly. This approach, too, can be tedious and relatively inefficient, as the approach requires a special-purpose cover sheet to be used for each job. Maintaining a supply of the proper cover sheets can be inconvenient.
Various one- and two-dimensional data codes are known and available to be used to store digital data on hardcopy documents. For example, various types of barcodes (for example, the familiar UPC symbol used as a retail product code) are very well known and are robustly decodable. Other examples of linear barcodes are known as Code 39, Code 128, Interleaved 2 of 5, and Postnet. Two-dimensional codes, such as the PDF417 code and the UPS MaxiCode used by the United Parcel Service to track packages, for example, are becoming more and more widespread.
Self-clocking glyph codes, such as Xerox DataGlyphs, are attractive for embedding machine-readable digital information in images of various types, including ordinary hardcopy documents. These codes have substantial tolerance to image distortion and noise because the digital information they encode is embedded in and fully defined by explicit machine-readable marks, for instance, “glyphs,” a term used herein which is not intended to be limited to Xerox DataGlyphs, but rather is intended to cover all machine-readable marks. These glyphs not only encode the information that is embedded in the code, but also define the sample clock that is employed to extract that information from the code, so they are responsible for the “self-clocking” property of the code as well as the distortion and noise tolerance.
Another known advantage of self-clocking glyph codes is that they ordinarily have an unobtrusive visual appearance, especially codes composed of glyphs that are written on a two-dimensional spatially periodic pattern of centers, such as a regular lattice-like pattern of centers, because the spatial periodicity of the glyphs causes the code to have a more-or-less uniformly textured appearance. For example, logically ordered single bit digital quanta typically is encoded by respective elongated slash-like glyphs which are written on a two-dimensional, spatially periodic pattern of centers in accordance with a predetermined spatial formatting rule, with the individual glyphs being tilted to the left or right of vertical by approximately +45° and −45° for encoding logical “0's” and “1's”, respectively. The mutual orthogonality of the glyph encodings for the two logical states of these single bit digital quanta enhances the discriminability of the code sufficiently to enable the embedded information to be recovered, even when the code pattern is written on a sufficiently fine grain pattern of center to cause the code pattern to have a generally uniform grayscale appearance. However, self-clocking glyph codes can be designed to encode multi-bit digital quanta in the glyphs.
Accordingly, providing a solution that facilitates the use of documents in the digital domain and the transition of documents from hardcopy to digital formats is desirable. Such a solution should be simple, efficient, convenient, and require little or no expertise on the part of the user.
A scheme of encoded tags, such as adhesive stickers or labels, is used to serve as the primary user interface in a hardcopy document processing system. Such a system would permit a user to specify an action or a service to be performed, along with his or her identity, simply by applying a sticker to the document and placing the document into a bin to be scanned.
The stickers are relatively small and unobtrusive, and, in one embodiment, use Xerox DataGlyphs to encode the user's identity, a desired service, and an optional argument for the service. The user maintains a supply of stickers corresponding to a particular service, for example, “scan and send to my personal e-mail account.” When the user desires that service to be performed, he simply applies one of the appropriate stickers to the document.
A computer system performing one embodiment operates by first accepting information on the user's identity. This information can be obtained, for example, by scanning and analyzing one of the user's business cards. This information is stored in a database and is given a unique user ID number. The user ID is combined with a desired service code, and the resulting data set is encoded into the desired printed data format. The system then prints a customized set of labels representing the user ID and service.
When the user wishes to have the service specified by his stickers performed, he or she simply applies one of the stickers to a document and places the document into a scanning queue. The document is scanned, the sticker is identified, decoded, and re-associated with the user's information retrieved from the database, and the desired service is performed.
As will be recognized, this system can be adapted to perform numerous services and actions, including but not limited to simply scanning and storing the document in a repository, faxing the document, converting the document into a standard electronic format, such as Microsoft Word format, and others.
One embodiment provides a user interface tag for use in processing a document. A printable surface is on one side of a document and an adhesive surface is on an other side of the document. The printable surface further includes a printed data field, including machine-readable marks of digital data encoding a service and a user identity; and a printed border surrounding the printed data field to define an iconic representation. A scanned representation of the machine-readable marks is decoded from the iconic representation to specify the user identity and the service.
A further embodiment provides a user interface tag for use in processing a service on a scannable document. A printable surface is on one side of a scannable document and an adhesive surface is on an other side of the scannable document. The printable surface further includes a printed data field specified substantially within the printable surface and including machine-readable marks of digital data encoding a service code and a user identification number. The printable surface further includes a printed rectilinear border surrounding the printed data field to define a rectilinear iconic representation. A scanned representation of the machine-readable marks is located by identifying the printed rectilinear border using corner candidates oriented in diametric opposition from among connected components identified on the document. The scanned representation of the machine-readable marks are decoded from the rectilinear iconic representation to specify the user identification number and the service code.
A still further embodiment provides a glyph-encoded user interface tag for use in processing a scannable document. A printable surface is on one side of a scannable document and an adhesive surface is on an other side of the scannable document. The printable surface further includes a printed data field, including machine-readable glyphs of digital data encoding a service code and a unique user identification number, and a printed border surrounding the printed data field to define an iconic representation. A scanned representation of the machine-readable glyphs is decoded from the iconic representation to specify the unique user identification number and the service code.
Accordingly, the sticker-based user interface is convenient and simple and does not require the user to enter commands on a computer system or fill out a cover sheet for every document to be processed. The sticker-based user interface is efficient as only the user is required to keep a supply of small stickers.
The invention is described below, with reference to detailed illustrative embodiments. The invention can be embodied in a wide variety of forms, some of which may be quite different from those of the disclosed embodiments. Consequently, the specific structural and functional details disclosed herein are merely representative and do not limit the scope.
Furthermore, while the user interface tag is illustrated in
As shown, the glyph sticker pattern 110 includes several important attributes. A substantially rectangular border 111 surrounds the remaining features and is, in turn, surrounded by white space 113. A glyph field 112 contains a printed representation of digital data used to perform the goals of the embodiment. The structure and contents of the glyph field 112 will be discussed in further detail below. For now, the glyph field 112 of
Other identifying elements may also be present within the glyph sticker pattern 110. For example, the Xerox “Digital X” 114 and the registered mark “PaperWare®” 116 are present and used for aesthetic purposes and as trademarks. The phrase “The Person” 118 is also present indicating that this field may be replaced with an indication of the user's name or other information for visual identification. There is also a border portion 120 that is representative of a folded page. This border portion 120 may be present for aesthetic purposes only, or may be used to facilitate determination of the correct orientation of the glyph sticker pattern 110. This aspect will be discussed in further detail below.
Referring now to
A service argument 214 provides a coded argument to the service code 212. In one embodiment, the argument 214 is an additional byte (eight bits) of information. For example, certain services may require a numeric argument, for example, “scan and print copies” followed by an argument of “10” will print ten copies. Other services may require a differently coded argument, for example, “scan and fax” followed by an argument of “2” may represent a command to fax the document to the user's home fax number, as opposed to an office fax number or, perhaps, an alternate office fax number, both of which would have different argument numbers. Many other uses of the service argument 214 may also be envisioned.
An identity code 216 comprises most of the rest of the data structure 210. In an embodiment, the identity code includes sixteen bytes of identity information, which is sufficient to encode a unique identification number for each member of nearly any conceivable population, and eight bytes of security information, rendering the identity code essentially tamper-proof. The identity information is formed from the network address, either an Ethernet address or an IP address, of the machine issuing the identity code, a time stamp, and a sequence number. Although, a number formed in this manner is not guaranteed to be unique under all circumstances, for example, if the database of sequence numbers is lost and the same time stamp is coincidentally used twice, this number is quite robust and sufficiently unique for the purposes of the embodiment. The identity code may be formed in any of numerous other ways and all of which would be acceptable for use.
The data structure 210 also includes error-correction and synchronization information throughout the specified data fields in a manner well known in the art and not shown in
When the user wishes to process a document, he attaches a glyph sticker onto the document and places the document into a scanner 320, which is a part of a “back end” 319 of the system. The scanner is preferably an automated scanner capable of handling multiple jobs and multi-page documents without user intervention. However, any other type of digitizing apparatus, such as, flatbed scanners, digital copiers, and hand-held scanners, would also be usable. The scanner 320 reads the document and formulates a bitmap representative of the document and the glyph sticker on the document.
An action processor 322 reads the bitmap received from the scanner 320, identifies and decodes the glyph sticker, and accesses the database server 316 to determine the identity of the user. The desired service may be known from accessing a list of possible services stored locally on the action processor 322, or may also be determined by accessing a service database on the database server 316, or alternatively may be inferred simply from the identity of the user.
Based on the user's identity and the desired service, the action processor 322 then causes the desired action to be performed, which may involve the generation of a transformed document by an output device 324. The output device 324 is characterized generally here, but as discussed above, may comprise a hardcopy printer, a facsimile machine or modem capable of sending fax messages, a network connection for e-mail, a connection to a document repository, a digital storage device, such as a floppy disk drive, or an aggregation of some or all of these and other functions.
While the system of
As suggested above by
First, the user or another person inputs information (step 410) into the system, typically via the data input 312 (
The user identity code 216, the service code 212, and the service argument 214 are then encoded and formed into a glyph field 112 representative of the information (step 416). The newly-created customized glyph field 112 is then printed any number of times as glyph sticker patterns 110 onto any desired number of stickers (step 418) for eventual use by the user.
The glyph sticker pattern 110 is then located on the document (step 512). In one embodiment, the glyph sticker pattern is located via a rectangle-matching method described below in conjunction with
Once the glyph sticker pattern 110 has been located, the data within the glyph field 112 is then decoded (step 514), which is accomplished via methods that will be discussed in further detail below, in connection with
One method used to locate user interface tags, for example, the glyph sticker pattern 110 of
The method is operative on monochromatic images, for instance, binary images represented with only one bit per pixel. If the digitized image is in some other format, such as color or grayscale, the digitized image should first, as a precursor to the method set forth in
The characteristics, for example, resolution, of the digitizing device used are expected to be known. Therefore, because the absolute size of the glyph sticker pattern 110 (
Accordingly, and based on the foregoing, the minimum and maximum expected diagonal measurements would be dmin=√{square root over ((w−Δw)2+(h−Δh)2)}{square root over ((w−Δw)2+(h−Δh)2)} and dmax=√{square root over ((w+Δw)2+(h+Δh)2)}{square root over ((w+Δw)2+(h+Δh)2)}, respectively.
After a suitable digitized image is available, all connected components within the image are initially identified (step 610). A connected component is a set of pixels of a single value, for example, the value representing black, wherein a path can be formed from any pixel of the set to any other pixel in the set without leaving the set, for example, by traversing only black pixels. In general terms, a connected component may be either “4-connected” or “8-connected.” In the 4-connected case, the path can move in only horizontal or vertical directions, so there are four possible directions. Accordingly, two diagonally adjacent black pixels are not 4-connected, unless there is another black pixel horizontally or vertically adjacent, serving as a bridge between the two. In the 8-connected case, the path between pixels may also proceed diagonally. One embodiment uses 8-connected components, but a 4-connected components could also be identified and used.
Because the border 111 of the glyph sticker pattern 110 (
The connected components within the image are identified by means known in the art, for instance, by starting with a single black pixel within the image, recursively locating all connected pixels until the connected component is fully defined, and repeating until all black pixels within the image belong to a connected component. However, other means of identifying connected components may also be used to equivalent effect.
Each connected component is then processed separately. If there are any connected components remaining to process (step 611), then the method continues as follows. If the connected component is too small (step 612), that is, if the width or height of the connected component is less than a minimum expected value, then the connected component is rejected (step 614). In one embodiment, the minimum expected value, used for both height and width, is the smaller of hmin and wmin to account for possible rotation of the pattern 110. Likewise, the connected component is rejected (step 614) if the connected component is too large (step 616), and the width or height of which exceeds the maximum expected value by a substantial amount. In one embodiment, the maximum expected value, for both height and width, is substantially larger than the greater of hmax and wmax to account for possible rotation. When the pattern 110 or any rectangle is oriented at an angle, the width and height of the pattern 110 may appear to be larger than expected, approaching or equaling dmax. Accordingly, a buffer is built into the latter check.
Eight extreme points, one for each of eight “compass positions,” are then selected (step 618) from the set of pixels comprising the connected component C. Each point has a position represented by an (x, y) coordinate pair, and represents a pixel of the connected component C that extends furthest in the selected direction (north, northeast, east, southeast, south, southwest, west, or northwest) within the image plane. Each extreme point is chosen as follows.
N=(xN,yN)εC|yN≦y∀(x,y)εC
E=(xE,yE)εC|xE≧x∀(x,y)εC
S=(xS,yS)εC|yS≧y∀(x,y)εC
W=(xW,yW)εC|xW≦x∀(x,y)εC
NE=(xNE,yNE)εC|(xNE−yNE)≧(x−y)∀(x,y)εC
SE=(xSE,ySE)εC|(xSE+ySE)≧(x+y)∀(x,y)εC
SW=(xSW,ySW)εC|(xSW−ySW)≦(x−y)∀(x,y)εC
NW=(xNW,yNW)εC|(xNW+yNW)≦(x+y)∀(x,y)εC
Various optimizations can be performed in identifying the eight extreme points. For example, if the connected component C is broken down into horizontal runs of contiguous pixels, then only the leftmost pixel in each run need be considered as a candidate for the NW, W, and SW extreme points, and only the rightmost pixel in each run need be considered as a candidate for the NE, E, and SE extreme points. Moreover, if the horizontal runs are ordered vertically, then only the endpoints of the uppermost and lowermost runs need be considered for the N and S extreme points. When the border 111 (
If the connected component C is the border 111, namely, a rectangle with one missing corner, then three of the extreme points will contain rectangular corner points (the folded-over corner will be offset), and the other five will contain irrelevant information. However, the method described herein has not yet determined whether the connected component C is the border 111, or if so, which extreme points represent the corners of the connected component C; that is determined as set forth below.
Consider, then, all eight extreme points. If the distance between any two diametrically opposed extreme points satisfies the diagonal length criteria (step 620), then the connected component is a border candidate. That is, if dmin≦∥N−S∥≦dmax, or if dmin≦∥E−W∥≦dmax, or if dmin≦∥NE−SW∥≦dmax, or if dmin≦∥SE−NW∥≦dmax, then a border candidate has been found. Otherwise, the connected component C is rejected (step 614).
Based on the position of the diagonal, the other two potential corners of the connected component are then identified (step 622) and considered. If the diagonal was found between either the N−S or E−W extremities, then the values of N, E, S, and W are used for p1, p2, p3, and p4, representing the four corner points of the border candidate, respectively. Similarly, if the diagonal was found between either the NE-SW or SE-NW extremities, then the values of NE, SE, SW, and NW are used for p1, p2, p3, and p4, the four corner points of the border candidate, respectively.
Then, relationships among the four points p1, p2, p3, and p4 are analyzed to determine whether a rectangular shape is present (step 624). In particular, the distances between p1 and p2, p2 and p3, p3 and p4, and p4 and p1 are all considered. At least one distance (of the four possible) should approximate the expected width, and at least one adjacent, but not the opposing, distance should approximate the expected height.
That is, if either
((wmin≦∥p1−p2∥≦wmax) or (wmin≦∥p3−p4∥≦wmax)) and ((hmin≦∥p2−p3∥≦hmax) or (hmin≦∥p4−p1∥≦hmax))
or
((hmin≦∥p1−p2∥≦hmax) or (hmin≦∥p3−p4∥≦hmax)) and ((wmin≦∥p2−p3∥≦wmax) or (wmin≦∥p4−p1∥≦wmax))
is true, then the connected component C is potentially the border 111, and is added to a list (step 626) of possible positions. If not, the connected component C is, once again, rejected (step 614).
As stated above, a list of potential positions is generated from all border candidates that satisfy the foregoing criteria. The entire list is then passed to the decode process (step 514 of
The foregoing method of identifying and locating the substantially rectangular border 111 of the glyph sticker pattern 110, in any orientation and with minor variations in scale, would be applicable to and useful in numerous other image-processing applications. The method illustrated in
Furthermore, minor variations of this method, readily apparent to those skilled in the art, may also be used to identify and locate various parallelogram, rhombus, trapezoid, and irregular quadrilateral patterns in addition to rectangles and rectangle-like shapes. In these alternative embodiments, either one or both of the diagonals can be checked; the two diagonals may have different expected lengths. In addition, the method can be extended to identify and locate n-sided polygons, by identifying extreme points at 2n evenly-spaced compass positions, and thereafter checking for vertices at alternating extreme points. Where n is an odd number, any diagonal found will not be diametric; however, any expected distance or a set of expected distances between adjacent or non-adjacent vertices, in nearly any n-sided polygon, can be used in a method, according to one embodiment, to identify the polygon within an image.
Once all of the glyphs have been located, the proper rotation of the glyph field 112 is determined (step 716). As can be seen in
As shown in
The method for determining the glyph lattice is based upon building up an average picture of what the local neighborhood of the glyph is, and from this average, determining the lattice vectors. In one embodiment, the method is implemented as follows (and as illustrated in
In the glyph image, that is, the area within the border 111, identify some number of pixels in the image as seed pixels for processing (step 910). These seed pixels may be, for example, spaced on a lattice of N×N pixels throughout the image, where N is of the order of 10-50 (the spacing may be chosen so that there are approximately 100 seed pixels throughout the glyph image 810).
Then, starting at each seed pixel, find the local minimum intensity in the image nearest that seed (step 912). If no local minimum is found within an appropriate distance of the seed pixel, (for example, 10 pixels), then move to the next seed pixel. The local minima, for instance, the darkest points in the bitmap, typically correspond to glyphs.
Once a local minimum is found, whether there is sufficient image contrast (step 914) between the region within 1 to 2 pixels of the minimum, (for instance, the center, and the region 3 to 4 pixels from the minimum, (for instance, the surrounding area) is determined. If the contrast is too small compared to the average image intensity surrounding the local minimum, then the method abandons further computation with the present local minimum, and moves to the next seed pixel in the glyph image, if there are any. This step, which may be left out if desired, is employed to screen out spurious local minima in the image resulting from noise and other non-glyph material.
Otherwise, the grayscale image surrounding the local minimum is added (step 916) to a composite image, which initially is filled with pixels of value zero. This composite image, which is built up during the processing, thus becomes a sum of the bitmap values around a number of local minima in the glyph image. The composite image is typically on the order of 20×20 pixels in dimension.
If there are any seed pixels remaining to be processed (step 918), then the process is repeated.
After finding the local minima associated with all of the seed pixels, the composite image is analyzed (step 920) to determine the average glyph locations. For example, the center of the composite image will necessarily be a local minimum, as the center of the composite image is composed of many images whose centers were minima. The nearest local minima to the center in the composite image will then correspond to the average nearest neighbor positions of the glyphs in the glyph lattice. Determination of these minima (step 922) in the composite image will therefore result in knowledge of the configuration of the glyph lattice; the lattice vectors 812 and 814 can then be derived (step 924).
The method described above and in conjunction with
From the glyphs' lattice vectors 812 and 814, a search direction list 1010 is generated. See
The operations performed in finding a seed glyph for the recognition process will be discussed in connection with
The seed glyph is found by looking at random locations in the images. At a chosen random location (step 1110), a set of correlation filters is applied over a 3×3 neighborhood of pixels adapted to cover the area of a single glyph (step 1112). The 3×3 neighborhood accommodates noise and small variations in the glyph lattice. The correlation filters that are applied depend upon the image skew determined from finding the lattice vectors 812 and 814. If the skew is between −22.5° and 22.5°, the following correlation filter kernels are applied:
If the skew is between −45° and −22.5°, the following kernels are applied:
If the skew is between 45° and 22.5°, the following kernels are applied:
The two correlation kernels are applied separately over the 3×3 neighborhood where a glyph is expected. Since the glyphs typically appear black, the minimum value of the two correlations is observed, and the difference between the two correlations is formed (step 1114) and compared to a threshold (step 1116):
v=min(K0*I3×3)−min(K1*I3×3)
where * denotes correlation. If the absolute value of v is less than a preset threshold (step 1118), the location does not contain a glyph. If v is positive, the glyph has a value of 0, and if v is negative, the glyph has a value of 1.
Once a glyph is found, the method looks for neighboring glyphs (step 1120) using the search direction list described above. The method stops looking for a seed glyph once the method has found a glyph with four neighboring glyphs (step 1122).
The final step in the recognition process is to determine the values of the individual glyphs and place these values into a matrix. One embodiment uses the search direction list (
The search FIFO list controls the clustering. As new glyphs are found, they are placed at the end of the search FIFO list. Essentially, the search FIFO list contains the locations in the image that need to be searched for neighboring glyphs. When the search FIFO list is empty, the process stops.
Beginning with the seed glyph, if any glyphs are present in the FIFO list (step 1312), the method pulls a glyph location from the FIFO list (step 1314). The glyph location value is determined (step 1316) and placed into the data matrix. The value of the glyph is determined by using the same correlation kernels used to find the seed glyph. The method then searches outward (step 1318) looking for neighboring glyphs using the search direction list (see
This method has several desirable features. First, this method can handle groups of glyphs with arbitrary boundaries. The glyph block need not be rectangular. Second, this method provides a clean method of dealing with scale and rotation variations. Finally, this method is tolerant to intensity gradients and markings placed on top of the glyphs. Although, a FIFO list is used in one embodiment, other search methods, including those that use a LIFO (last-in-first-out) stack or a list based on some other ordering scheme, such as a position within the image, can also be used with similar effect.
Finally, as discussed above, the data matrix is used as shown in
While certain exemplary embodiments have been described in detail above, other forms, alternatives, modifications, versions, and variations are equally operative and would be apparent to those skilled in the art. The disclosure is not intended to limit the invention to any particular embodiment, and is intended to embrace all such forms, alternatives, modifications, versions, and variations.
This patent application is a continuation of U.S. Pat. No. 7,168,036, issued Jan. 23, 2007 the priority filing date of which is claimed, and the disclosure of which is incorporated by reference.
Number | Name | Date | Kind |
---|---|---|---|
5065437 | Bloomberg | Nov 1991 | A |
5084769 | Miura | Jan 1992 | A |
5091966 | Bloomberg et al. | Feb 1992 | A |
5131049 | Bloomberg et al. | Jul 1992 | A |
5159180 | Feiler | Oct 1992 | A |
5202933 | Bloomberg | Apr 1993 | A |
5288976 | Citron et al. | Feb 1994 | A |
5343558 | Akeley | Aug 1994 | A |
5449895 | Hecht et al. | Sep 1995 | A |
5666214 | MacKinlay et al. | Sep 1997 | A |
5790429 | Baker et al. | Aug 1998 | A |
5825933 | Hecht | Oct 1998 | A |
5836622 | Fabel | Nov 1998 | A |
5857790 | Gutsell et al. | Jan 1999 | A |
5939699 | Perttunen et al. | Aug 1999 | A |
5956419 | Kopec et al. | Sep 1999 | A |
5974202 | Wang et al. | Oct 1999 | A |
5998752 | Barton et al. | Dec 1999 | A |
6144848 | Walsh et al. | Nov 2000 | A |
6192165 | Irons | Feb 2001 | B1 |
6208771 | Jared et al. | Mar 2001 | B1 |
6427020 | Rhoads | Jul 2002 | B1 |
RE38758 | Bloomberg et al. | Jul 2005 | E |
Number | Date | Country |
---|---|---|
0469864 | Feb 1992 | EP |
0483936 | May 1992 | EP |
05284264 | Oct 1993 | JP |
Number | Date | Country | |
---|---|---|---|
20070116358 A1 | May 2007 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 09192014 | Nov 1998 | US |
Child | 11656385 | US |