Patent Application
20080128593
This application is based on and claims priority under 35 USC 119 from Japanese Patent Application No. 2006-323789 filed Nov. 30, 2006.
1. Technical Field
The present invention relates to an image processing device, image reading device, and image forming device.
2. Related Art
To scan an object such as a document to be imaged by using an image forming device having a scanner device, reflection light from the document is detected within wavelength ranges of three colors, namely, red, green, and blue by a light receiving element such as a line sensor while illuminating the document with light. The image forming device generates multi-valued image data which includes four color components of yellow, magenta, cyan, and black through a predetermined image process of, for example, obtaining spectral reflectancespectral reflectances in the respective wavelength ranges. The more the number of colors that can be detected by the light receiving element, the more the number of colors that can be expressed by combinations of spectral. reflectancespectral reflectances within the respective wavelength ranges. Accordingly, images can be formed with colors of the original object reproduced with more fidelity. Hence, there has long been a demand for a technique by which it is possible to detect a high range of wavelengths of reflection light reflected from an object to be imaged; i.e., a technique for reading an object in as many colors as possible.
According to one aspect of the invention, there is provided an image processing device including: a spectral reflectancespectral reflectance calculation unit that calculates a spectral reflectancespectral reflectance within a wavelength range including wavelengths of visible light, for each of at least two types of irradiation light having respectively different spectral energy distributions, on the basis of intensities of reflection light reflected from an object to be imaged when the object to be imaged is irradiated with at least two types of irradiation light and on the basis of irradiation intensities of at least two types of irradiation light; a color value calculation unit that obtains color values based on the spectral reflectancespectral reflectances calculated by the spectral reflectancespectral reflectance calculation unit; a coefficient calculation unit that calculates coefficients respectively for a plurality of predetermined eigenvectors where the color values are expressed by a linear combination between the plurality of predetermined eigenvectors, the coefficients, and spectral energies of at least two types of irradiation light; and an output unit that generates and outputs information corresponding to estimation values within a wavelength range defined by excluding at least one of low and high wavelength ranges from the wavelength range including the wavelengths of visible light, among estimation values of the spectral reflectancespectral reflectances expressed by a linear combination between the respective coefficients calculated by the coefficient calculation unit and the eigenvectors.
Exemplary embodiments of the present invention will be described in detail based on:
Exemplary embodiments for practicing the invention will now be described. The following description will be made referring to a case where an object O to be imaged is a sheet-like object, for example. However, the object O to be imaged is not limited only to a sheet-like object such as an OHP sheet or the like but may have any type of shape. In the embodiments, a “visible light range” refers to a range of wavelengths of approximately 380 to 780 nm.
The image reading unit 10 has a function of a so-called image scanner. The image forming unit 20 has a function of a so-called printer. The image reading unit 10 includes a platen glass 11, platen cover 12, full-rate carriage 13, half-rate carriage 14, imaging lens 15, and line sensor 16.
The platen glass 11 is a glass plate on which the object O to be imaged is put. The platen glass 11 is provided with surfaces positioned horizontally. On a surface of the platen glass 11, a reflex inhibition layer made of a multi-layered dielectric film or the like is formed to reduce reflection on the surface of the platen glass 11. The reflex inhibition layer is provided to prevent a reflection light component from the surface of the object O to be imaged, which has to be read primarily, from being read synthesized with an unnecessary reflection light component from the surface of the platen glass 11. Aiming for separation between the reflection light component from the object O and the reflection light component from the surface of the platen glass 11, the surface of the object O to be imaged and the surface of the platen glass 11 may be set apart from each other by a predetermined clearance, for example, by providing a spacer. The platen cover 12 is provided so as to cover the platen glass 11. External light is shielded by the platen cover 12 to facilitate reading of the object O put on the platen cover 11.
A structure of the full-rate carriage 13 mentioned above will now be described in detail.
As the wavelength increases within the visible light range, the spectral energy of this light increases linearly. In the first embodiment, a tungsten lamp is used as a light source for light A.
As shown in
Referring again to
The imaging lens 15 and a prism 17 are provided on a light path connecting the mirror 142 and the line sensor 16, and images light reflected from the object O to be imaged at the position of the line sensor 16.
Referring again to
Each of sheet feed trays 21 contain sheets of a predetermined size and feed the sheets along with image formation. In this case, the sheets are paper sheets normally used for image formation, such as PPC (Plain Paper Copier) sheets. If necessary, paper sheets coated with resins or the like or sheets made of material other than paper may be used. The conveyor rolls 22 for a conveyor path for conveying sheets fed from the sheet feed trays 21 to a position where the secondary transfer roll 25 faces the backup roll 26. The conveyor path for sheets is drawn by a broken line in
Referring to
The image forming unit 20 uses toners of total nine colors for development, which include four primary colors of cyan, magenta, yellow and black, as well as red, orange, green, and blue (toners for the eight colors noted are referred to as “color toners”), and still further a transparent color (a toner for the transparent color is referred to as a “transparent toner”). The transparent toner contains no coloring material and includes a low-molecular-weight polyester resin externally added with SiO2 (silicon dioxide), TiO2 (titanium dioxide), or the like. A toner image consisting of the transparent toner is formed over an entire image to reduce gaps which are caused by a difference in toner amount at every position on the image. Accordingly, surface roughness of the image becomes inconspicuous. Toners as described above are contained at appropriate positions in the primary transfer units 23a, 23b, and 23c, depending on use frequencies. However, only the transparent toner should desirably be transferred prior to color toners. This is because the transparent toner is transferred so as to cover color toners on the surface of each sheet.
Referring again to
The secondary transfer mechanism 29 has a fixing belt 291, heater 292, and heat sink 293. In the secondary transfer mechanism 29, the heater 292 further heats a sheet which has once been heated and pressed for fixing by the primary fixing mechanism 27. Toners are thereby changed into a molten state. The secondary transfer mechanism 29 then cools the sheet by the heat sink 293 to fix toners, maintaining the sheet in contact with the fixing belt 291 having a smooth surface. Through this fixing process, toner images may be formed with flat and smooth surfaces and with high glossiness.
Outline of the image forming process will now be described.
The full-rate carriage 13 in the image forming unit 20 scans an object O to be imaged by irradiating the object with light from the first light source 131 or the second light source 132 (this process will be hereinafter referred to as a “scanning operation”). In particular, a scanning operation using the first light source 131 to irradiate the object O is referred to as a “first scanning operation”, and image data to be generated therefrom is referred to as “first image data”. Another scanning operation using the second light source 132 to irradiate the object O is referred to as a “second scanning operation”, and image data to be generated therefrom is referred to as “second image data”. That is, the image reading unit 10 carries out two of the first and second scanning operations. The image processing unit 50 generates the first and second data from image signals obtained by the scanning operations, respectively, and calculate spectral reflectancespectral reflectances.
In an image forming device according to a related art, spectral reflectancespectral reflectances are not treated as continuous values but treated as discrete values. That is, a predetermined number of spectral reflectancespectral reflectances are calculated (or extracted) from wavelength ranges which are included in a visible light range and used actually for process of image forming and the like. Hereinafter, a “spectral reflectancespectral reflectance estimation function” refers to a function (a continuous value) for obtaining an estimated value by performing regression analysis or the like on “spectral reflectancespectral reflectances” (discrete values) extracted from particular wavelength ranges.
If spectral reflectancespectral reflectances are regarded as being of a continuous value as is originally meant, the continuous value draws a curve along which the value varies smoothly. In many cases where spectral reflectancespectral reflectances are extracted as discrete values, a spectral reflectancespectral reflectance estimation function may be obtained with satisfactory accuracy by supposing a wavelength interval δ=10 nm. If the wavelength interval δ=10 nm is set and if a wavelength range from which spectral reflectancespectral reflectances should be extracted is set to 400 to 700 nm within a visible light range, thirty one spectral reflectancespectral reflectances are extracted per pixel. In case of using an image forming device having a commonly used structure, an object to be imaged is scanned within only three wavelength ranges of R, G, and G, and therefore, only three signals per pixel need to be transferred via signal lines or a bus. If the image forming device with the commonly used structure should extract thirty one spectral reflectancespectral reflectances per pixel, a total number of spectral reflectancespectral reflectances extracted from an entire image data should be (extracted spectral reflectancespectral reflectances per pixel)×(the number of pixels). Consequently, a huge number of values which is about ten times greater than in normal cases with the commonly used structure have to be transferred via signal lines or a bus. Such data transfer requires a prolonged period to merely transfer spectral reflectancespectral reflectances as data.
To reduce the amount of data expressing spectral reflectancespectral reflectances to be transferred by the image forming device, the amount of data of m spectral reflectancespectral reflectances extracted at wavelength intervals δ has to be reduced. More specifically, m spectral reflectancespectral reflectances are expressed by a linear combination of a small number n of eigenvectors than m. That is, if coefficients may be determined for predetermined n eigenvectors, spectral reflectancespectral reflectance estimation functions having various characteristics may be uniquely determined. Accordingly, the data amount may be reduced. However, to reduce the data amount in this manner, the number n of eigenvectors should be desirably small. On the other hand, to reduce differences between spectral reflectancespectral reflectance estimation functions and original spectral reflectancespectral reflectances of an object to be imaged, spectral reflectancespectral reflectances having various characteristics need to include eigenvectors whose contributing rates are relatively high.
The following describes in detail why spectral reflectancespectral reflectances may be expressed by eigenvectors having relatively high contributing rates. As described above, spectral reflectancespectral reflectances are originally continuous amounts. Many of such continuous values are of wavelength ranges in which the continuous values are expressed smoothly as curves in accordance with changes of the wavelength. In other words, spectral reflectancespectral reflectances whose wavelength ranges are close to each other have close values in many cases. This is due to the fact that two light spectrums of close wavelength ranges have similar characteristics. When an object to be imaged is irradiated with such two light spectrums, intensities of the spectrums of reflection light reflected from the object have also close characteristics. Therefore, a spectral reflectancespectral reflectance of a wavelength range may be considered to be correlative to a spectral reflectancespectral reflectance of another wavelength range, and may also be considered to accompany existence of a eigenvector having a relatively large contributing rate. Accordingly, an equation of a spectral reflectancespectral reflectance estimation function by use of a eigenvector may be an effective measure to reduce a data amount.
There will be further be described a procedure for calculating a spectral reflectancespectral reflectance estimation function by use of a eigenvector as described above.
A manner of defining a eigenvector will now be described. At first, a population is defined by spectral reflectancespectral reflectances for a huge number of colors which are supposed to be included in an object to be imaged. Further, a multivariate analysis (e.g., principal content analysis is adopted in the following) is carried out on the population, to define a eigenvector. Since a spectral reflectancespectral reflectance estimation function may be expressed, for every color, by using a linear combination of eigenvectors, the population should desirably include spectral reflectancespectral reflectances for as many colors as possible, which do not have close spectral reflection characteristics.
Next, eigenvectors are defined as principal content analysis is performed on the population.
A spectral reflectancespectral reflectance estimation function expressed by linear combination of the eigenvector e1i(λ) is expressed as ρ1(λ). The eigenvector e1i(λ) has a characteristic which varies as the calculation method of the principal content analysis varies.
Though
In view of the accumulated contributing rate when the number of eigenvectors is seven or higher, the accumulated contributing rate does not substantially increase but stays flat. That is, if the number n of the eigenvectors exceeds a certain value, only the data amount increases and the accuracy of the spectral reflectancespectral reflectance estimation function does not substantially improve. On the other hand, if the number of eigenvectors is five or smaller, the data amount of the spectral reflectancespectral reflectance estimation function decreases further. However, in this case, the accumulated contributing rate relative to the population Σ drops sharply. For example, if the number of eigenvectors is set to two, the accumulated contributing rate relative to the population Σ is about 60%. With this rate, the spectral reflectancespectral reflectance estimation functions cannot attain satisfactory accuracy even for spectral reflectancespectral reflectances constituting the population Σ. Therefore, the number of eigenvectors should desirably be selected balancing the accumulated contributing rate relative to a defined population of eigenvectors and a data amount required for the accumulated contributing rate.
Subsequently, a relationship between the eigenvectors e11(λ) to e16(λ) and the spectral reflectancespectral reflectance estimation function ρ1(λ) is expressed by a relation equation 1 below. In the following, thirty one spectral reflectancespectral reflectances (m=31) at a wavelength interval δ=10 nm within a wavelength range of 400 to 700 nm are extracted from each of the pixels constituting first and second image data.
The equation 1 is to calculate the spectral reflectancespectral reflectance estimation function ρ1(λ) by linearly combining the eigenvectors e11(λ) to e16(λ) with coefficients w11 to w16. The coefficients w11 to w16 are unknown values.
Further, color values corresponding to the spectral reflectancespectral reflectances obtained from the first and second image data. Optimal coefficients w11 to w16 are calculated on the basis of a relationship between the color values and the spectral reflectancespectral reflectances estimation function ρ1(λ) represented by the equation 1. Provided that the color values are stimulus values on XYZ color coordinates, the coefficients w11 to w16 are calculated uniquely by the following equations 2 to 7. The equations 2 to 7 are known as relation equations between spectral reflectancespectral reflectances and stimulus values on the XYZ color coordinates, and the spectral reflectancespectral reflectance estimation function ρ1(λ) is used in this case. The equations 2 to 4 relate to an example of standard light D65, and equations 5 to 7 relate to an example of standard light A.
In the equations 2 to 7, “vis-” denotes a wavelength range within a visible light range, from which spectral reflectancespectral reflectances are extracted, e.g., 400 to 700 nm in the first embodiment. E65(λ) is an equation indicative of a spectral energy distribution of light from the first light source 131. EA(λ) is an equation indicative of a spectral energy distribution of light from the second light source 132. Functions expressed with overbars added to x, y, and z of x(λ), y(λ), and z(λ) are respectively color-matching functions about x-axis, y-axis, and z-axis on the XYZ color coordinates.
Thirty one spectral reflectancespectral reflectances are extracted from each of the pixels forming the first and second image data. For each of the spectral reflectancespectral reflectances, stimulus values XD65, YD65, ZD65, XA, YA, and ZA are obtained. The equations 2 to 7 are then simplified into first-degree equations with six coefficients w11 to w16 as unknown values, respectively. Accordingly, a unique value is calculated for each of the coefficients w11 to w16. After the values of the coefficients w11 to w16 are calculated, the image forming device 1 may obtain the spectral reflectancespectral reflectance estimation function ρ1(λ) and may determine colors and amounts of toners which are required when forming an image. Since the stimulus values XD65, YD65, ZD65, XA, YA, and ZA have already been obtained, the user may roughly estimate colors from the stimulus values.
Next, a specific operation procedure to be carried out by the image forming device 1 will be described. In a manufacturing phase, to define six eigenvectors e11(λ) to e16(λ) in advance, principal content analysis is carried out manually or by the image forming device 1, on a population Σ consisting of spectral reflectances for various colors which may be supposed to be included in an object to be imaged. The defined eigenvectors e11(λ) to e16(λ) are stored in an internal memory in the image processing unit 50 or the like.
According to
Subsequently, the image processing unit 50 calculates XD65, YD65, ZD65, XA, YA, and ZA on the XYZ color coordinates for each of the pixels forming first and second data, based on the spectral reflectances calculated in the step S5 (step S6). Further, the image processing unit 50 calculates the coefficients w11 to w16 to obtain a spectral reflectance estimation function ρ1(λ) (step S7).
Subsequently, the image processing unit 50 executes a color space processing and a screen processing on image data, and determines colors and amounts of toners to be applied to areas corresponding to respective pixels of the image data (step S8).
When determining toner amounts, the controller 30 specifies mixing ratios between colors of toners (or coloring materials) of cyan, magenta, yellow, black, red, orange, green, and blue and shapes of screen dots for each pixel, depending on the colors expressed by the spectral reflectance estimation function ρ1(λ). The controller 30 may further determine whether or not a transparent toner should be used, depending on an image expressed by the image data. For example, if the image data is a monochrome document data which requires toners of a small number of colors, the controller 30 sets zero as a toner amount of the transparent toner. Otherwise, if the image includes a lot of colors, i.e., if toners of a large number of colors are used, the controller 30 applies a predetermined amount of transparent toner to the entire surface of the image data.
The controller 30 supplies the image forming unit 20 with the image data including information indicative of mixing ratios, area ratios, and screen dots concerning toners of respective colors for each pixel (step S9). Based on the image data, the image forming unit 20 forms an image on a recording sheet P (step S10) using plural toners.
At this time, the image forming unit 20 selects primary transfer units 23 corresponding to image data for respective colors, and forms electrostatic latent images based on the image data. Thereafter, the image forming unit 20 selects developing units to match the toner colors indicated by the image data, and applies toners to the electrostatic latent images, to form toner images. Toner images for respective colors are thus formed and each color is transferred to the intermediate transfer belt 24. The image forming unit 20 further secondarily transfers the toner images to a sheet, and fixes the toner images by the primary fixing mechanism 27 and secondary fixing mechanism 29. The sheet is then discharged outside. In this manner, a copy of an image representing the object O to be imaged is formed, and the image forming process is concluded.
The first embodiment is configured as described above.
A second embodiment of the invention will now be described.
In the second embodiment, the spectral reflectance may be calculated more accurately than in the first embodiment.
In
The present inventors have presumed the following reasons why differences between a spectral reflectance estimation function ρ1(λ) and the original spectral reflectances of an object to be imaged are large only within the low and high wavelength ranges.
From the reasons as described above, differences between the spectral reflectance estimation function ρ1(λ) and original spectral reflectances of an object to be imaged increase within the low and high wavelength ranges.
In view of the above, in the second embodiment, spectral reflectances are calculated throughout a substantially entire wavelength range (380 to 780 nm) of the visible light range, which is higher than the wavelength range of 400 to 700 nm used in the actual process of image forming or the like. If a spectral reflectance estimation function is obtained on the basis of the spectral reflectances, only the spectral reflectance estimation function within the medium wavelength range of 400 to 700 nm is used for image forming process or the like, excluding the low wavelength range of 380 to 780 nm and the high wavelength range of 700 to 780 nm from the wavelength range of visible light. In this manner, differences between the spectral reflectance estimation function and the spectral reflectances of an object to be imaged may be considered to decrease within the medium wavelength range.
Such consideration has resulted from the reasons as follows.
As shown in
Referring to
A solid curve C2 in
From the reasons described above, the image forming device 1 calculates a spectral reflectance estimation function for 380 to 780 nm, and therefore extracts spectral reflectances in this wavelength range. Accordingly, the second embodiment uses a line sensor 16a in place of the line sensor 16 in the first embodiment.
The manner of defining the eigenvectors is the same as that in the first embodiment except that the target wavelength range is from 380 to 780 nm.
Next, a relationship between the eigenvectors e11(λ) to e16(λ) and the spectral reflectance estimation function ρ1(λ) is expressed by a relation equation 8 below. In the following, forty one spectral reflectances (m=41) at wavelength intervals of δ=10 nm within the wavelength range of 380 to 780 nm are extracted from each of the pixels constituting first and second image data.
The equation 8 is to calculate the spectral reflectance estimation function ρ2(λ) by linearly combining the eigenvectors e21(λ) to e26(λ) with coefficients w21 to w26. The coefficients w11 to w16 are unknown values.
Further, color values are obtained on the basis of spectral reflectances calculated from the first and second image data. Optimal coefficients w21 to w26 are calculated from a relationship between the color values and the spectral reflectances estimation function represented by the equation 8. Provided that the color values are stimulus values on XYZ color coordinates, the coefficients w21 to w26 are calculated uniquely by the following equations 9 to 14. The equations 9 to 11 relate to an example of standard light D65, and equations 12 to 14 relate to an example of standard light A.
The equations 9 to 11 express relationships between stimulus values x(λ), y(λ), and z(λ) obtained by a first scanning operation and values of the spectral reflectance estimation function ρ2(λ). The equations 12 to 14 express relationships between stimulus values x(λ), y(λ), and z(λ) obtained by a second scanning operation and values of the spectral reflectance estimation function ρ2(λ). In the equations 9 to 14, “vis-” denotes a substantial visible light range from which spectral reflectances are extracted, e.g., 380 to 780 nm in this case. Functions expressed with overbars added to x, y, and z of x(λ), y(λ), and z(λ) are respectively color-matching functions about x-axis, y-axis, and z-axis on the XYZ color coordinates.
Forty one spectral reflectances are extracted from each of the pixels forming the first and second image data. For each of the spectral reflectances, stimulus values XD65, YD65, ZD65, XA, YA, and ZA are obtained. The equations 9 to 14 are then simplified into first-degree equations with six coefficients w21 to w26 as unknown values, respectively. Accordingly, a unique value is calculated for each of the coefficients w21 to w26.
In this manner, differences between the spectral reflectance estimation function ρ2(λ) and the original spectral reflectances of an object to be imaged are obtained for one thousand of the various objects to be imaged. As a result, the differences between the function and the factors fall within a range of approximately 6% or so which is smaller than in the first embodiment described previously.
According to
Subsequently, the image processing unit 50 calculates XD65, YD65, ZD65, XA, YA, and ZA on the XYZ color coordinates for each of the pixels forming first and second data, based on the spectral reflectances calculated in step S51 (step S16). Further, the image processing unit 50 calculates the coefficients w21 to w26 to obtain a spectral reflectance estimation function ρ2(λ) (step S17).
Subsequently, based on values of the spectral reflectance estimation function ρ2(λ) within the medium wavelength range of 400 to 700 nm, the image processing unit 50 executes a color space processing and a screen processing on image data and determines colors and amounts of toners to be applied to areas corresponding to the respective pixels of the image data (step S18).
When determining toner amounts, the controller 30 specifies mixing ratios between colors of toners (or coloring materials) of cyan, magenta, yellow, black, red, orange, green, and blue and also specifies shapes of screen dots for each pixel, depending on colors expressed by values of the spectral reflectance estimation function ρ2(λ) determined by the coefficients w21 to w26 within the medium wavelength range of 400 to 700 nm. The controller 30 may further determine whether or not a transparent toner should be used, depending on an image expressed by the image data. For example, if the image data is a monochrome document data which requires toners of a small number of colors, the controller 30 sets zero as a toner amount of the transparent toner. Otherwise, if the image has a lot of colors, i.e., if toners of a large number of colors are used, the controller 30 applies a predetermined amount of a transparent toner to the entire surface of the image data.
The controller 30 supplies the image forming unit 20 with the image data including information indicative of mixing ratios, area ratios, and screen dots concerning toners of respective colors for each pixel (step S19). Based on the image data, the image forming unit 20 forms an image on a recording sheet P (step S20) using plural toners.
The second embodiment is configured as described above.
The first and second embodiments as described above may be modified as follows. The following modifications may be arbitrarily combined with one another.
The above embodiments have been described as reference examples to the image processing unit 50 built in the image forming device 1. However, the image processing unit is not limited to a structure in which an image processing unit is built in an image forming device. The image processing unit may be included in, for example, a computer which executes image processing. In this case, the image forming device performs necessary processing on the basis of values of a spectral reflectance estimation function expressed by linear combination of coefficients and eigenvectors obtained as described above, within the visible light range excluding low and high wavelength ranges. Information obtained by the processing is output to an external device such as an image forming device. The information may represent amounts of plural coloring materials, which the image forming device calculates, or may present the spectral reflectance estimation function itself. At the same time, the image processing device may output stimulus values together. According to this modification, a user of the information processing device supplied with the information may visually check stimulus values and determine colors, with the stimulus values displayed on a display device (not shown).
In the second embodiment, amounts of coloring materials and the like are calculated using stimulus values x(λ), y(λ), and z(λ) related to a wavelength range defined by excluding the low wavelength range of (380 to 780 nm) and the high wavelength range of (700 to 780 nm) from the wavelength range of 380 to 780 nm. However, only the low or the high wavelength range may be a target wavelength range to be excluded. For example, in order to obtain accurately stimulus values x(λ), y(λ), and z(λ) about a range of 400 to 440 nm or so, only the “low wavelength range” needs to be set as a target wavelength range to be excluded. Inversely, only the “high wavelength range” needs to be set as a target wavelength range to be excluded, in order to obtain accurately stimulus values x(λ), y(λ), and z(λ) about a range of 660 to 700 nm or so.
Also in the second embodiment, a target wavelength range for which stimulus values x(λ), y(λ), and z(λ) are calculated is set to 380 to 780 nm. Of this target wavelength range, the low wavelength range is set to 380 to 780 nm and the high wavelength range is set to 700 to 780 nm. These numerical values are merely examples and may be changed.
In the above embodiments, the first light source 131 has been described as a light source for irradiating standard light D65, as well as the second light source 132 as a light source for irradiating standard light A. However, any type of light source may be used as far as spectral energy distributions of the first and second light sources differ from each other within a wavelength range for which a spectral reflectance estimation function is obtained. Independently from types of light sources, six is the number of stimulus values obtained on the basis of spectral reflectances extracted from the image data, and is thus equal to the number of eigenvectors. Accordingly, coefficients may be calculated uniquely from relation equations such as equations 2 to 7 and 9 to 14 representing relationships between the stimulus values and the eigenvectors, to specify a spectral reflectance estimation function.
Although the above embodiments have described the number of eigenvectors to be six, the number of eigenvectors is not limited to six. As shown in
However, in order to uniquely calculate coefficients for the nine eigenvectors, first-degree equations, each having nine coefficients is required concerning stimulus values. That is, nine different stimulus values need to be obtained. It is therefore necessary to perform scanning operations using different three light sources. Specifically, a third scanning operation is carried out using a light source for irradiating auxiliary standard light D50 in addition to first and second scanning operations. The auxiliary standard light D50 is a light source having a color temperature of 5,000 K and has a substantially uniform spectral energy distribution throughout the visible light range of about 400 to 700 nm (approximately uniform within a range of 380 to 780 nm). According to this modification, coefficients for all the nine eigenvectors may be uniquely calculated from relationships between the nine different stimulus values and the spectral reflectance estimation function.
Also in the above embodiments, the image forming device 1 uses stimulus values on the XYZ color coordinates, as color values. As an alternative, color values according to CIELAB color space may be used. Stimulus values on the XYZ color coordinates are desirable to determine what colors are expressed on a certain observation condition. However, stimulus values on the XYZ color coordinates are inconvenient for clearly expressing differences between colors. In this respect, difference between colors may be expressed quantitatively by using color values according to the CIELAB color space. Therefore, color values according to the CIELAB color space are convenient, for example, when in need of distinguishing a slight difference between colors. As a further alternative, there may be a method of obtaining coefficients by using stimulus values on the XYZ color coordinates and then converting the stimulus values into color values according to the CIELAB color space. Otherwise, color values according to other color space may be used in place of values according to the CIELAB color space.
Also in the above embodiments, toner images are formed using toners of eight colors and a transparent toner wherein the eight colors are cyan, magenta, yellow, black, red, orange, green, and blue. Colors used in the invention are not limited to these colors. One or more arbitrary toners among these toners may be contained in an image forming device to perform developing.
The first embodiment employs a line sensor having thirty one columns of light receiving elements, and the second embodiment employs forty one columns. However, the number of columns of light receiving elements may be more or less than thirty one and forty one. The second embodiment is then required to be able to receive light of a necessary wavelength range, so that processing is carried out within a medium wavelength range defined by excluding a low and a high wavelength ranges from a visible light range, for the spectral reflectance estimation function. In view of a purpose of reading more colors from an object than three colors of R, G, and B as read by related arts, at least four columns of light receiving elements are required. Even with use of one single column of light receiving elements, there is an available method of scanning one object plural times while switching plural color filters.
The foregoing description of the embodiments of the present invention has been provided for the purposes of illustration and description. It is not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations will be apparent to practitioners skilled in the art. The embodiments were chosen and described in order to best explain the principles of the invention and its practical applications, thereby enabling others skilled in the art to understand the invention for various embodiments and with the various modifications as are suited to the particular use contemplated. It is intended that the scope of the invention be defined by the following claims and their equivalents.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2006-323789 | Nov 2006 | JP | national |
