Image reading apparatus and image forming apparatus

Abstract

To provide an image reading device and an image forming device that improve the accuracy of foreign object detection. [Solution] In the image reading device, the reading means (CIS117, 119) includes an image sensor for reading the original document, a light source for illuminating the original document with illumination light, and a rod lens array for focusing reflected light from the original document onto the image sensor. The storage means (memory 211) pre-stores reference color data acquired by reading the reference color plate with the reading means as comparison data when no foreign matter is attached to the reference color plate. The detection means (CPU 201) detects foreign matter based on the reference color data and comparison data acquired by reading the reference color plate with the reading means before reading the original document. Here, the reference color data and comparison data are each subjected to filtering. The filtering is a filtering process that corresponds to the periodic characteristics derived from the rod lens array.

Description

Technical Field

[0001] The present invention relates to an image reading apparatus and an image forming apparatus.

Background Art

[0002] An image reading apparatus reads a white reference plate before reading a document, and applies shading correction to the reading result of the document using the read value. Thereby, variations in the distribution of the illumination light amount and variations in the sensitivity for each pixel of the image sensor are corrected. However, if foreign substances such as paper dust, ink, or toner adhere to the white reference plate, the shading correction fails. Therefore, according to Patent Document 1, it has been proposed to determine the presence or absence of pixel abnormalities based on data obtained by previously reading a reading reference surface and data obtained by subsequently reading the reading reference surface. According to Patent Document 1, it has also been proposed to consider data related to the fluctuation range of the reading value based on temperature changes.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a contact image sensor (CIS), a rod lens array may be used as an imaging optical system. When the temperature of the image sensor changes, the relative positional relationship between the rod lens array and the image sensor fluctuates. As a result, it has been found that the detection accuracy of foreign substances decreases. Therefore, an object of the present invention is to improve the detection accuracy of foreign substances.

Means for Solving the Problems

[0005] The present invention is, for example, A reading means comprising an image sensor for reading a document, a light source for illuminating the document with illumination light, and a rod lens array for focusing reflected light from the document onto the image sensor, A reference color plate is positioned opposite the reading means, A storage means that stores the reference color data obtained by reading the reference color plate with the reading means when no foreign matter is attached to the reference color plate, as comparison data, A detection means for detecting foreign objects based on reference color data obtained by reading the reference color plate with the reading means before reading the aforementioned document, and the comparison data, A filter that applies a filter processing corresponding to the periodic characteristics derived from the rod lens array to the input value to obtain an output value and outputs the said output value, It has, The detection means provides an image reading device that detects foreign objects based on the reference color data to which the filtering process has been applied and the comparison data to which the filtering process has been applied. [Effects of the Invention]

[0006] According to the present invention, the accuracy of detecting foreign objects is improved. [Brief explanation of the drawing]

[0007] [Figure 1] This is a diagram illustrating the structure of an image reading device. [Figure 2] This is a diagram illustrating an image processing circuit. [Figure 3] This is a diagram illustrating a rod lens array. [Figure 4] This diagram illustrates the relationship between readings and foreign objects. [Figure 5] This is a diagram illustrating a method for detecting foreign objects. [Figure 6] This is a diagram illustrating a method for detecting foreign objects. [Figure 7] This is a diagram illustrating a method for detecting foreign objects. [Figure 8] This is a diagram illustrating a method for detecting foreign objects. [Figure 9] This is a diagram for explaining the functions realized by the CPU. [Figure 10] This is a diagram for explaining a method of reducing the influence of foreign matter. [Figure 11] This is a flowchart for explaining an image reading method. [Figure 12] This is a diagram for explaining a method of detecting foreign matter. [Figure 13] This is a flowchart for explaining an image reading method. [Figure 14] This is a diagram for explaining a method of detecting foreign matter. [Figure 15] This is a diagram for explaining a method of detecting foreign matter.

Mode for Carrying Out the Invention

[0008] Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. Note that the following embodiments do not limit the invention according to the claims. Although a plurality of features are described in the embodiments, not all of these plurality of features are essential to the invention, and the plurality of features may be arbitrarily combined. Further, in the accompanying drawings, the same reference numerals are assigned to the same or similar configurations, and duplicate explanations are omitted.

[0009] <Example 1> 1. Image reading apparatus In FIG. 1, an image reading apparatus 100 is an image reading apparatus including an automatic document feeder (ADF) 131 and a reading unit 121.

[0010] 1-1. Structure of the ADF The original document tray 101 includes a support plate that supports the loaded original document 102. Above the original document tray 101, a feed roller 103 is provided. The feed roller 103 is connected to the same drive source (e.g., a motor) as the first separation roller 104. The feed roller 103 rotates as the drive source rotates and feeds the original document. The feed roller 103 normally retracts to an upper position which is its home position, facilitating the user's operation of setting the original document. When the feeding operation is started, the feed roller 103 descends and abuts against the upper surface of the original document 102.

[0011] The first separation roller 104 and the second separation roller 105 are conveying rollers arranged on the downstream side of the feed roller 103 in the conveying direction of the original document 102. The first separation roller 104 and the second separation roller 105 are arranged to face each other. The second separation roller 105 is biased against the first separation roller 104. The frictional force of the conveying surface of the second separation roller 105 is slightly less than the frictional force of the conveying surface of the first separation roller 104. The second separation roller 105 cooperates with the first separation roller 104 to separate one original document 102 from a plurality of original documents 102 fed by the feed roller 103 and convey it further downstream.

[0012] The registration roller 106 and the registration driven roller 107 are arranged further downstream than the first separation roller 104 and the second separation roller 105. The registration roller 106 and the registration driven roller 107 are conveying rollers that correct the skew of the original document 102.

[0013] Downstream of the registration roller 106 and the registration driven roller 107, a lead roller 108 and a lead driven roller 109 are arranged. The registration roller 106 and the registration driven roller 107 convey the original document 102 toward the platen glass 116. Above the platen glass 116, a platen roller 110 is arranged.

[0014] A CIS 117 is positioned below the slide-reading glass 116. CIS is an abbreviation for contact image sensor. The CIS 117 acquires image information from the surface of the document 102 being transported over the slide-reading glass 116 and generates an image signal or image data. A jump ramp 115 is positioned downstream of the platen roller 110. The jump ramp 115 scoops up the document 102 being transported toward the slide-reading glass 118 and directs the document 102 toward the slide-reading glass 118.

[0015] The CIS 119 is positioned above the pan-read glass 118. The white reference plate 120 is positioned below the pan-read glass 118. The CIS 110 reads the white reference plate 120 through the pan-read glass 118 before the document 102 arrives at the reading position to obtain a correction factor for shading correction. The CIS 119 then reads the image information from the back of the document 102 as it is transported over the pan-read glass 118 to create an image signal or image data.

[0016] Downstream of the CIS119 are the discharge roller 111 and the driven roller 112. The discharge roller 111 and the driven roller 112 transport the document 102 further downstream. Downstream of the discharge roller 111 and the driven roller 112 are the discharge roller pair 113. The discharge roller pair 113 discharges the document 102 into the discharge tray 114.

[0017] 1-2. Structure of the reading unit The reading unit 121 includes a CIS 117 and a white reference plate 122. The CIS 117 is coupled to a drive motor (not shown) by a belt (not shown) and moves parallel to the document glass 130 by the rotational drive of the drive motor.

[0018] The CIS117 comprises a lamp 123, a rod lens array 124, and a line sensor 125. The lamp 123 is a light source that illuminates the document 102 with illumination light. The light emitted from the lamp 123 (image light) is reflected from the surface of the document 102 and incident on the rod lens array 124. The rod lens array 124 has multiple rod lenses and is an imaging optical system that forms an image of the image light on the light-receiving part of the line sensor 125. The line sensor 125 is an image sensor that has multiple light-receiving elements (photoelectric conversion elements) arranged parallel to the main scanning direction and outputs an electrical signal according to the amount of incident light.

[0019] The CIS119 includes a lamp 126, a rod lens array 127, and a line sensor 128. The lamp 126 is a light source for illuminating the document 102. Light (image light) emitted from the lamp 126 is reflected off the back surface of the document 102 and incident on the rod lens array 127. The rod lens array 127 has multiple rod lenses and is an imaging optical system that forms an image of the image light on the light-receiving part of the line sensor 128. The line sensor 128 has multiple light-receiving elements (photoelectric conversion elements) arranged parallel to the main scanning direction and outputs an electrical signal corresponding to the amount of incident light.

[0020] The image reading device 100 has a fixed reading mode and a scrolling reading mode. In the fixed reading mode, the document 102 fixed on the document glass 130 is read by the CIS 117 which moves parallel to the sub-scanning direction. In the scrolling reading mode, the front surface of the transported document 102 is read by the CIS 117 and the back surface of the document 102 is read by the CIS 119.

[0021] 2. Image Processing Circuit Figure 2 shows the image processing circuit of the image reading device 100.

[0022] 2-1. Surface Image Processing The CPU201 outputs a drive signal to the CIS117. The CIS117 reads the document 102 according to the drive signal and outputs an analog image signal. The ADC202 is an analog-to-digital converter controlled by the CPU201 that converts the analog image signal input from the CIS117 into a digital image signal (image data).

[0023] Image data is input to an image processing circuit 204 controlled by the CPU 201. The image processing circuit 204 is an application-specific integrated circuit (ASIC) that applies various image processing to the image data. The image processing circuit 204 may be implemented on the CPU 201. The image processing circuit 204 includes shading correction circuits 205 and 207, and shading memories 206 and 208. The shading correction circuit 205 corrects the image data using correction coefficients stored in the shading memory 206. Shading correction is an image processing that reduces sensitivity unevenness of the light-receiving elements included in the line sensor 125. The image processing circuit 204 outputs the image data to the printer 210. The printer 210 is an image forming means that forms an image corresponding to the image data on a sheet.

[0024] 2-2. Image processing of the reverse side The CPU201 outputs a drive signal to the CIS119. The CIS119 reads the document 102 according to the drive signal and outputs an analog image signal. The ADC203 is an analog-to-digital converter controlled by the CPU201 that converts the analog image signal input from the CIS119 into a digital image signal (image data).

[0025] Image data is input to an image processing circuit 204 controlled by the CPU 201. The shading correction circuit 207 corrects the image data using correction coefficients stored in the shading memory 208. This reduces sensitivity unevenness of the light-receiving elements included in the line sensor 128. The image processing circuit 204 outputs the image data to the printer 210. The printer 210 forms an image on a sheet corresponding to the image data.

[0026] The CIS119 may have a non-volatile memory 211. The memory 211 stores control information, which will be described later.

[0027] 3. Creation of correction coefficients When the CPU 201 is instructed by the user to perform image reading, it creates a correction coefficient for shading correction. In other words, the creation of the correction coefficient is performed immediately before reading the original document 102. The correction coefficient is a coefficient used to correct for variations in the light intensity distribution of the reading optical system in the main scanning direction, and variations in the sensitivity of each pixel of the line sensors 125 and 128. The white reference plates 120 and 122 are reference color plates with uniform whiteness and are used to create the correction coefficient. In the following description, the white reference plate 120 will be explained as an example, but the same applies to the white reference plate 122.

[0028] The CPU 201 or the shading correction circuit 207 performs the following calculations based on the image data acquired by reading the white reference plate 120 with the CIS 119. This yields the gain value (correction coefficient SHD) for each pixel (e.g., 1 to 7344 pixels × 3 colors).

[0029] SHD(x) = WHtrg ÷ WHIin(x) ···Eq.1 Here, x represents the main scan position (e.g., 1-7344). WHtrg is the target brightness value of the white reference plate 120. WHIin(x) is the reading (brightness value) of the white reference plate 120. The correction coefficient SHD is stored in the shading memory 208.

[0030] The CPU 201 causes the CIS 119 to read the image of the document 102. The shading correction circuit 207 performs shading correction on the image data of the document 102 acquired by the CIS 119 using the correction coefficient SHD.

[0031] Iout(x) = Iin(x) × SHD(x) ···Eq.2 Here, x represents the main scanning position (1 to 7344). Iin(x) is the luminance value for each pixel obtained from the original document 102. Iout(x) is the luminance value for each pixel after shading correction.

[0032] Shading correction reduces the effects of variations in light intensity distribution in the main scanning direction and variations in sensitivity for each pixel of line sensors 125 and 128. In other words, image data with less brightness unevenness can be obtained.

[0033] Thus, the shading correction circuits 205 and 208 have the function of creating a correction coefficient SHD and the function of applying shading correction to image data using the correction coefficient SHD. It is not essential that both functions be implemented in the shading correction circuits 205 and 208. The function of creating the correction coefficient SHD may be implemented in the CPU 201.

[0034] 4. Foreign object detection Foreign matter may adhere to the optical path from the white reference plate 120 to the line sensor 128. When foreign matter adheres, the accuracy of the correction coefficient SHD decreases, and the performance of shading correction deteriorates. Therefore, the following describes a method for detecting foreign matter (e.g., paper dust, ink, toner) adhering to the white reference plate 120. The same applies to the white reference plate 122.

[0035] If a correction coefficient is obtained while foreign matter (e.g., black toner) is attached to the white reference plate 120, the brightness value of the pixels corresponding to the foreign matter attached to the white reference plate 120 will decrease. As a result, the correction coefficient SHD will become larger than the ideal value. When shading correction is applied to the image data of the original document 102, the brightness value of a specific main scanning position will increase more than necessary. As a result, white streaks parallel to the sub-scanning direction will appear.

[0036] Therefore, the CPU 201 or the shading correction circuit 207 detects when foreign matter adheres to the white reference plate 120 during the acquisition of the correction coefficient SHD, and creates a correction coefficient SHD with the influence of the foreign matter reduced.

[0037] 5. Periodic irregularities originating from the rod lens array Figure 3 is an enlarged view of the CIS119. Inside the CIS119 is a rod lens array 127. The rod lens array 127 is an optical component that focuses light irradiated onto the document surface onto the light-receiving surface of the line sensor 128. The rod lens array 127 has a plurality of rod lenses arranged along a direction perpendicular to the document transport direction (main scanning direction).

[0038] The refractive index of the rod lens changes from the central axis towards the outer edge. In other words, the refractive index distribution is not uniform. Therefore, even when the reflected light from the document surface is uniform, the amount of light focused onto the light-receiving surface of the line sensor 128 fluctuates with a period corresponding to the rod lens pitch Prl. This can also be called periodic unevenness.

[0039] Figure 4(A) shows an example of the reading (luminance value) of the white reference plate 120. The horizontal axis indicates the pixel position x. The vertical axis indicates the luminance value. The reflectance of the white reference plate 120 is uniform. However, the reading (luminance value) of the white reference plate 120 is affected by the non-uniformity of the lamp 126, the sensitivity variation of each pixel of the line sensor 128, and the periodic unevenness originating from the rod lens array 127.

[0040] Figure 4(B) shows the reading when a black foreign object is attached to the white reference plate 120. Figure 4(C) is a magnified view of the area (first region) where the foreign object is attached. The luminance value obtained from the white reference plate 120 includes the non-uniformity of the lamp 126, the sensitivity variation of each pixel of the line sensor 128, and the periodic unevenness of the rod lens array 127. Therefore, there are foreign objects 2 that can be detected using a threshold and foreign objects 1 that cannot be detected using a threshold.

[0041] In Example 1, initial data, which guarantees that the white reference plate 120 is free of foreign matter, is compared with reference color data obtained by actually reading the white reference plate 120 with the CIS 119, and foreign matter is detected. The initial data is comparison data that is compared with the reference color data. The initial data is reference color data obtained by reading the white reference plate 120 with the CIS 119 under conditions where it is guaranteed that the white reference plate 120 is free of foreign matter. The initial data is obtained, for example, at a factory that manufactures the image reading device 100 and stored in the memory 211.

[0042] The initial data and the reference color data are data acquired by the same CIS119. In other words, the sensitivity variation per pixel of the line sensor 128 and the periodic unevenness of the rod lens array 127 included in the initial data and the reference color data are identical. Therefore, the CPU 201 can detect foreign objects by comparing the initial data and the reference color data. Furthermore, since the non-uniformity of the lamp 126 is sufficiently greater than the non-uniformity caused by foreign objects, the non-uniformity of the lamp 126 can be easily distinguished.

[0043] Incidentally, the temperature of the CIS119 at the time of initial data acquisition (during manufacturing) may differ from the temperature of the CIS119 at the time of reference color data acquisition. In this case, the rod lens array 127 expands (contracts) due to thermal expansion, which can cause a shift in the relative position between the rod lens array 127 and the line sensor 128, depending on the main scanning position.

[0044] Figure 5(A) shows initial data and reference color data acquired by the same CIS119 at different temperatures. The horizontal axis indicates the pixel position. The vertical axis indicates the luminance value. Figure 5(B) is a magnified view of the luminance values ​​in the first region. The first region contains pixels affected by foreign object 1 and pixels affected by foreign object 2.

[0045] The central areas of the rod lens array 127 and the central areas of the line sensor 128 are fixed to the CIS 119. Therefore, even if the temperature fluctuates in the central area during the main scanning direction, the relative positional relationship between the rod lens array 127 and the line sensor 128 does not change.

[0046] The first region is located near the center of the white reference plate 120. As shown in Figure 5(B), in the first region, the brightness values ​​of pixels affected by foreign object 1 and the brightness values ​​of pixels affected by foreign object 2 are reduced.

[0047] Figure 5(C) illustrates the ratio calculation for detecting foreign objects 1 and 2 in the first region. Here, the ratio is the ratio between the initial data and the reference color data for each pixel. A difference may be used instead of the ratio.

[0048] In the first region, the phase of unevenness in the initial data and the phase of unevenness in the reference color data are in the same phase. Therefore, the ratio becomes lower at the location of the foreign object, and the foreign object can be accurately detected using a predetermined threshold. For example, the threshold is set to 0.95 times the average value of the ratios of N pixels (e.g., 100 pixels) surrounding the pixel of interest. In other words, the threshold is set lower than the average value of the N ratios obtained for N pixels surrounding the pixel of interest.

[0049] Figure 6(A) is a magnified view of the luminance values ​​in the second region. The second region is the area at the edge of the white reference plate 120. The second region contains pixels affected by foreign matter 3 and pixels affected by foreign matter 4. As shown in Figure 6(A), in the second region, the luminance values ​​of pixels affected by foreign matter 3 and pixels affected by foreign matter 4 are reduced. Furthermore, the left and right ends of the line sensor 128 are significantly shifted relative to the left and right ends of the line sensor 128 due to thermal expansion (contraction). As a result, the phase of unevenness in the initial data and the phase of unevenness in the reference color are out of sync.

[0050] Figure 6(B) is a diagram illustrating the ratio calculation for detecting foreign objects 3 and 4 in the second region. As shown in Figure 6(B), foreign object 4 can be detected in the second region based on the ratio and threshold. However, detection of foreign object 3 fails. This is because in the second region, the phase of unevenness in the initial data and the phase of unevenness in the reference color data are not in phase. Therefore, in Example 1, it is required that foreign object 3 also be detectable.

[0051] Therefore, in Example 1, filtering is applied to both the initial data and the reference color data according to the periodic characteristics (e.g., pitch Prl) of the rod lens array 127. As a result, the CPU 201 accurately detects foreign objects based on the filtered initial data and the filtered reference color data. In other words, the influence of the difference between the relative positional relationship between the rod lens array 127 and the line sensor 128 when acquiring the initial data and the relative positional relationship between the rod lens array 127 and the line sensor 128 when acquiring the reference color data is reduced. Specifically, the periodic unevenness of the rod lens array 127 in the initial data is reduced by filtering, and the periodic unevenness of the rod lens array 127 in the reference color data is reduced by filtering. Then, by comparing the initial data with reduced unevenness and the reference color data with reduced unevenness, pixels affected by foreign objects become apparent. In other words, foreign objects are no longer hidden by unevenness.

[0052] 6. Filtering Figure 7(A) shows the initial data and reference color data in the first region. Figure 7(B) shows the effect of applying a filter to the initial data and reference color data in the first region. Figure 8(A) shows the initial data and reference color data in the second region. Figure 8(B) shows the effect of applying a filter to the initial data and reference color data in the second region.

[0053] The filtering process in Example 1 is applied to M pixels, consisting of the pixel of interest and the pixels surrounding it. M may also be called the filter width. As an example, let's assume M = 7, because the pitch Prl of the rod lens array 127 corresponds to approximately 7 pixels. In other words, M is the integer or multiple of the period of the unevenness originating from the pitch Prl of the rod lens array 127. The filtering process can be any process that can reduce the periodic unevenness of the brightness value originating from the rod lens array 127. Here, a moving average is used as the filtering process. The filtering process can be expressed, for example, by the following calculation formula.

[0054]

number

[0055] Here, M is assumed to be an odd number. Here, x represents the main scan position (1 to 7344). Iin(x) is the brightness value of one pixel input to the filtering process. Iout(x) is the brightness value of one pixel output from the filtering process.

[0056] For example, if M=7, equation Eq.3 expands as follows:

[0057] Iout(x) = {Iin(x-3) + Iin(x-2) + Iin(x-1)+Iin(x)+Iin(x+1)+ Iin(x+2)+Iin(x+3)}÷7 ···Eq.3' The filtering process homogenizes the periodic (7-pixel periodic) unevenness originating from the rod lens array 127. As a result, the decrease in brightness value caused by the influence of foreign matter becomes apparent. Fluctuations in brightness value caused by unevenness in the lamp 126 and sensitivity variations of the line sensor 128, which are unrelated to the periodic characteristics of the rod lens array 127, are maintained.

[0058] The filter width M should be the number of pixels corresponding to the pitch Prl (period of unevenness) of the rod lens array 127. Furthermore, the filter width M may be adjusted depending on the pixel size of the line sensor 128 and the reading resolution. For example, suppose the pitch Prl of the rod lens array 127 is 300 μm and the pixel pitch of the CIS 119 is 42.3 μm. μm is an abbreviation for micrometer. In this case, the filter width M is calculated from the following equation.

[0059] M=300um / 42.3um ≒ 7 ···Eq.4 Incidentally, according to equations Eq. 3 and Eq. 3', the filter coefficients are both set to 1. However, this is just one example. The filter coefficients should be any coefficients that can reduce the periodic unevenness originating from the rod lens array 127. For example, the filter coefficients may be determined experimentally or by simulation at the time of factory shipment of the CIS119 and stored in memory 211.

[0060] As shown in Figure 7(B), the ratio and threshold are determined from the filtered initial data and the filtered reference color data, and foreign objects 1 and 2 present in the first region are detected. By calculating the ratio between the initial data and the reference color data, the unevenness of the lamp 126 and the sensitivity variation of the line sensor 128 are reduced, and foreign objects are detected with high accuracy.

[0061] As shown in Figure 8(B), a ratio and threshold are determined from the filtered initial data and the filtered reference color data, and foreign objects 3 and 4 present in the second region are detected. By calculating the ratio between the initial data and the reference color data, the unevenness of the lamp 126 and the sensitivity variation of the line sensor 128 are reduced, and foreign objects are detected with high accuracy. In particular, as shown in Figure 8(B), it can be seen that foreign object 3 can also be detected using the threshold.

[0062] 7. CPU Functions Figure 9 shows the functions implemented by the CPU 201. One or more of the functions shown in Figure 9 may be implemented in the image processing circuit 204. For example, these functions may be implemented in the shading correction circuits 205 and 207.

[0063] The filter 901 applies a filter to the input image data, which is the luminance value Iin(x), to generate output image data, which is the luminance value Iout(x), and outputs the output image data to the ratio calculation unit 902. The input image data is either reference color data or initial data. In other words, the filter 901 also applies a filter to the initial data read from the memory 211, and outputs the filtered initial data to the ratio calculation unit 902. This reduces periodic unevenness originating from the rod lens array 127 contained in the reference color data and the initial data, respectively. In the filtered reference color data, the effects of foreign matter become apparent.

[0064] The coefficient setting unit 911 is optional and reads filter coefficients from memory 211 and sets them in the filter 901. The width setting unit 912 is optional and reads the filter width M from memory 211 and sets it in the filter 901. The filter 901 performs filtering using equation Eq.3 or equation Eq.3'.

[0065] The ratio calculation unit 902 calculates the ratio R between the initial data to which the filter processing has been applied and the reference color data (output image data) to which the filter processing has been applied. The ratio calculation unit 902 outputs the ratio R to the determination unit 903 and the threshold setting unit 913.

[0066] The threshold setting unit 913 calculates the average value Rave of N ratios R, including the ratio R of the pixel of interest, and determines a threshold Rth such that it is lower than the average value Rave. The N ratios R are the ratios R obtained for the pixel of interest and the surrounding pixels located around it. The threshold setting unit 913 may also determine the threshold Rth by subtracting a margin Rm from the average value Rave. Alternatively, the threshold setting unit 913 may determine the threshold Rth by multiplying the average value Rave by a predetermined magnification mag (e.g., 0.95). The predetermined magnification mag can be a number less than 1. For example, N is 100.

[0067] The determination unit 903 determines whether a pixel of interest is affected by a foreign object by comparing the ratio R of the pixel of interest with the threshold Rth. If the ratio R of the pixel of interest is greater than or equal to the threshold Rth, it is determined that the pixel of interest is not affected by a foreign object. If the ratio R of the pixel of interest is less than the threshold Rth, it is determined that the pixel of interest is affected by a foreign object.

[0068] The correction unit 904 corrects the brightness value of the pixel of interest based on the determination result (foreign object detection result) from the determination unit 903. This corrects the brightness value of the pixel affected by the foreign object in the reference color data.

[0069] Figure 10(A) shows that there are pixels affected by foreign matter in the third region in the main scanning direction. Figure 10(B) is a magnified view of the third region. Foreign matter pixels refer to pixels affected by foreign matter attached to the white reference plate 120. Figure 10(C) shows the correction process for foreign matter pixels.

[0070] For example, the correction unit 904 calculates the brightness value of a pixel of interest by applying interpolation to the brightness values ​​of multiple pixels adjacent to the pixel of interest in the main scanning direction. The brightness value of the pixel of interest is then supplied to the shading correction circuits 205 and 207 and used to calculate the correction coefficient SHD. The correction coefficient SHD is stored in the shading memories 206 and 208.

[0071] According to Figure 10(C), the brightness value Y3 of the foreign pixel is calculated as an interpolated value (average value) of the brightness value Y1 of the preceding pixel and the brightness value Y2 of the following pixel.

[0072] Y3 = Y1 + (Y2 - Y1) ÷ 2 ... Eq. 5 Thus, the brightness value Y3 of a foreign pixel may be calculated by interpolating the brightness value Y1 of the preceding pixel and the brightness value Y2 of the following pixel.

[0073] Here, it is assumed that there is one foreign pixel, but there may be multiple consecutive foreign pixels. In this case as well, the brightness values ​​of the multiple foreign pixels may be corrected by interpolation using a front pixel located in front of the multiple foreign pixels and a back pixel located behind the multiple foreign pixels in the main scanning direction.

[0074] 8. Flowchart Figure 11 is a flowchart showing the image reading process performed by CPU 201. Here, the skimming mode in which CIS 119 is operating is executed.

[0075] In S1101, the CPU 201 acquires initial data. The CPU 201 may also read the initial data stored in memory 211. As described above, the initial data is the reference color data acquired by CIS 119 when no foreign matter is attached to the white reference plate 120.

[0076] In S1102, the CPU201 samples reference color data. For example, the CPU201 drives the CIS119 to read the white reference plate 120. Furthermore, the CPU201 converts the analog image signal output from the CIS119 into a digital image signal (image data) using the ADC203. For example, the initial data is image data consisting of the luminance values ​​of all pixels acquired for the white reference plate 120. All pixels refer to, for example, the 7344 pixels arranged in the main scanning direction for each of the three RGB colors. Therefore, the total number of pixels included in all pixels is 22032.

[0077] In S1103, CPU201 filters the initial data and reference color data. As described above, CPU201 generates output image data by applying filtering (e.g., moving average) to the input image data.

[0078] In S1104, CPU201 compares the filtered initial data with the filtered reference color data. For example, CPU201 calculates the ratio R between the filtered initial data and the filtered reference color data. In other words, the ratio R is an example of the comparison result.

[0079] In S1105, CPU201 detects foreign pixels based on the comparison results. For example, CPU201 selects the x-th pixel in the main scanning direction as the pixel of interest and calculates the ratio R(x) and threshold Rth(x). Furthermore, CPU201 detects pixels where the ratio R(x) is less than the threshold Rth(x) as foreign pixels.

[0080] In S1106, CPU201 interpolates the reference color data. For example, CPU201 determines the brightness value of a foreign pixel by interpolating the brightness value of the pixel before the foreign pixel with the brightness value of the pixel after it. Note that interpolation is not necessary for normal pixels that are not foreign pixels, and S1106 is skipped.

[0081] In S1107, the CPU 201 calculates a correction coefficient SHD for shading correction using the interpolated reference color data. The CPU 201 may also control the shading correction circuits 205 and 207 to calculate the correction coefficient SHD. The CPU 201 stores the correction coefficient SHD in the shading memories 206 and 208.

[0082] In S1108, CPU201 controls CIS117 and CIS119 to read the original document 102. In S1109, CPU201 controls shading correction circuits 205 and 207 to apply a correction coefficient SHD to the reading result (image data) of the original document 102 and perform shading correction.

[0083] According to Example 1, filtering reduces periodic irregularities originating from the rod lens array 127, which are present in both the initial data and the reference color data. As a result, even if the phase of irregularities in the initial data and the phase of irregularities in the reference color data are misaligned due to temperature changes in the rod lens array 127, foreign object pixels will become apparent. Consequently, foreign objects adhering to the white reference plate 122 can be detected with high accuracy.

[0084] Although the above-described embodiment 1 is mainly applied to CIS119, it is also applicable to CIS117. In other words, in the above description, CIS119, rod lens array 127, and shading correction circuit 207 are replaceable with CIS117, rod lens array 124, and shading correction circuit 205. CIS117 also has a non-volatile memory 211, where initial data obtained by CIS117 reading the white reference plate 122 may be stored.

[0085] In Example 1, the rod lens array 127 is an example of a rod lens array that focuses reflected light from the document 102 onto the image sensor. The white reference plate 120 is an example of a reference color plate positioned opposite the reading means (e.g., CIS 119). The memory 211 is an example of a storage means that stores reference color data acquired by reading the reference color plate with the CIS 119 when no foreign matter is attached to the reference color plate as comparison data. The CPU 201 functions as a detection means that detects foreign matter based on the reference color data and comparison data acquired by reading the reference color plate with the CIS 119 before reading the document 102. The filter 901 is an example of a filter that applies a filter processing corresponding to the periodic characteristics (e.g., pitch Prl) derived from the rod lens array 127 to the input value to obtain an output value and outputs the output value. The CPU 201 detects foreign matter based on the filtered reference color data and the filtered comparison data. This improves the accuracy of foreign matter detection.

[0086] The CPU201 may obtain the difference or ratio R between the filtered reference color data and the filtered comparison data as a comparison result, and detect foreign objects based on the comparison result.

[0087] The filter 901 may be configured to perform a moving average on the M input values ​​input to the filter 901 to obtain an output value and output that output value. Here, M may be the integer or multiple of the period derived from the rod lens array 127 that is closest to it. This reduces the unevenness of the luminance values ​​derived from the rod lens array 127 from the reference color data and the initial data.

[0088] As shown in Figure 3, the period of the rod lens array 127 may correspond to the period of the pitch Prl between adjacent rod lenses in the rod lens array 127.

[0089] The comparison data may also be reference color data acquired by CIS119 when there are no foreign objects in the optical path from the reference color plate (e.g., white reference plate 120) to the image sensor (e.g., line sensor 128).

[0090] The CPU 201 may detect foreign objects based on the comparison result and the threshold Rth. The CPU 201 may also determine the threshold Rth based on the brightness values ​​of N pixels surrounding the pixel of interest that is the basis of the comparison result. This will allow for more accurate detection of foreign object pixels.

[0091] CPU201 may determine a threshold Rth such that it is less than the average value of the brightness values ​​of N pixels, where N (e.g., 100) is an integer greater than M (e.g., 7).

[0092] CPU201 may determine the threshold by multiplying the average brightness value of N pixels by a magnification mag less than 1. Alternatively, CPU201 may determine the threshold by subtracting a margin from the average brightness value of N pixels, because the brightness value of a foreign pixel will be lower than that of the surrounding pixels.

[0093] The CPU 201 and the correction unit 904 function as correction means for correcting the reference color data according to the detection result. The shading memory 208 functions as a holding means for holding the correction coefficient SHD for shading correction determined based on the corrected reference color data. The shading correction circuit 207 functions as a correction means for correcting the image data of the original acquired by the CIS 119 using the correction coefficient SHD. According to Embodiment 1, the correction coefficient SHD is obtained from reference color data in which the influence of foreign object pixels has been reduced, so the accuracy of shading correction will also be improved.

[0094] For example, the correction unit 904 may correct or interpolate the image data of the pixel in which a foreign object was detected from the reference color data using image data of multiple pixels in the reference color data for which no foreign object was detected. As suggested by Figure 10(C), the multiple pixels for which no foreign object was detected include at least two pixels that are located around the pixel in which the foreign object was detected.

[0095] As shown in Figure 2, an image forming apparatus is provided that includes an image reading device 100 and an image forming means (printer 210) that forms an image on a sheet based on image data generated by the image reading device 100. This improves the reproducibility of the image copied onto the sheet.

[0096] <Example 2> In Example 1, a ratio R is calculated based on filtered initial data and filtered reference color data, and foreign pixels are detected based on ratio R. In Example 2, a ratio R is calculated based on unfiltered initial data and unfiltered reference color data. Furthermore, in Example 2, filtering is applied to ratio R, and foreign pixels are detected based on the filtered ratio R. The threshold Rth is determined from the filtered ratio R.

[0097] 1. Filtering Figure 12 shows the functions implemented in the CPU 201 or the image processing circuit 204. Functions in Figure 12 that are the same as those shown in Figure 9 are given the same reference numerals. Compared to Figure 9, in Figure 12, the filter 1202 is connected after the ratio calculation unit 1201.

[0098] The ratio calculation unit 1201 calculates the input ratio Rin(x) based on the initial data that has not been filtered and the reference color data that has not been filtered. The input ratio Rin(x) output from the ratio calculation unit 1201 is input to the filter 1202.

[0099] The filter 1202 calculates the output ratio Rout(x) by applying a filter to the input ratio Rin(x). The output ratio Rout(x) is input to the determination unit 903.

[0100]

number

[0101] Here, M is assumed to be an odd number. When M=7, equation Eq.6 is expanded as follows:

[0102] Rout(x) = {Rin(x-3) + Rin(x-2) + Rin(x-1)+Rin(x)+Rin(x+1)+ Rin(x+2)+Rin(x+3)}÷7 ···Eq.6' The threshold setting unit 913 calculates the average value Rave(x) of N ratios Rin(x-0.5(N-1)), ..., Rin(x+0.5(N-1)) ..., including the ratio Rin(x) of the pixel of interest, and determines the threshold Rth(x) to be lower than the average value Rave(x). For example, the threshold Rth(x) may be determined by subtracting a margin Rm from the average value Rave(x). Alternatively, the threshold Rth(x) may be calculated by multiplying the average value Rave(x) by a predetermined magnification mag (e.g., 0.95). The predetermined magnification mag is a number less than 1.

[0103] The determination unit 903 detects foreign pixels based on whether the output ratio Rout(x) is less than the threshold Rth(x). The operation of the coefficient setting unit 911, the width setting unit 912, and the correction unit 904 is as described in Example 1.

[0104] 2. Flowchart Figure 13 is a flowchart showing the image reading process in Example 2. The difference between Figure 13 and Figure 11 is that S1103 and S1104 have been replaced with S1303 and S1304.

[0105] In S1303, CPU201 compares the initial data with the reference color data. For example, CPU201 calculates the input ratio Rin(x) based on the unfiltered initial data and the unfiltered reference color data.

[0106] In S1304, CPU201 filters the comparison results. For example, CPU201 calculates the output ratio Rout(x) by applying a filter to the input ratio Rin(x). In S1105, CPU201 detects foreign pixels based on the filtered comparison result, output ratio Rout(x). CPU201 determines the threshold Rth(x) according to the method described in Example 1 and compares the output ratio Rout(x) with the threshold Rth(x).

[0107] Figure 14(A) shows the ratio R when foreign objects 1 and 2 are present in the first region shown in Figure 5(A). Here, ratio R is the unfiltered ratio. Since the first region is located near the center in the main scanning direction of the CIS119, the unfiltered ratio R can also indicate the location of the foreign object pixels. This is because, in the first region, the phase of the unevenness contained in the initial data and the phase of the unevenness contained in the reference color data are almost in phase.

[0108] Figure 14(B) shows the relationship between the ratio Rout and the threshold Rth calculated by Example 2. Based on the filtered ratio Rout and threshold Rth, foreign object pixels affected by foreign object 1 and foreign object pixels affected by foreign object 2 are detected with high accuracy.

[0109] Figure 15(A) shows the ratio R when foreign objects 3 and 4 are present in the second region shown in Figure 5(A). The second region is located near the edge in the main scanning direction. Here, the ratio R is not filtered. In the second region, the phase of the unevenness contained in the initial data and the phase of the unevenness contained in the reference color data are different. As a result, unevenness occurs in the ratio R due to the phase shift. Therefore, if the CPU 201 uses an unfiltered ratio R for pixels near the edge in the main scanning direction, it becomes difficult to detect foreign object 3.

[0110] Figure 15(B) shows the relationship between the ratio Rout and the threshold Rth calculated in Example 2. Based on the filtered ratio Rout and threshold Rth, foreign object pixels affected by foreign object 3 and foreign object pixels affected by foreign object 4 are detected with high accuracy.

[0111] According to Example 2, the filtering process reduces periodic irregularities in the ratio R that originate from the rod lens array 127. In particular, irregularities that originate from changes in the positional relationship between the rod lens array 127 and the line sensor 128, which depend on temperature changes, are reduced. As a result, foreign matter adhering to the white reference plate 122 can be detected with high accuracy.

[0112] In particular, according to Embodiment 2, the filter 1202 applies filtering based on the periodic characteristics derived from the rod lens array 127, using the comparison result as an input value. The CPU 201 and the determination unit 903 detect foreign objects using the filtered comparison result. This improves the accuracy of foreign object detection. The ratio calculation unit 1201 is an example of an acquisition means that obtains the difference or ratio between reference color data and comparison data obtained by reading the reference color plate with the CIS 119 before reading the original document 102 as a comparison result.

[0113] The invention is not limited to the embodiments described above, and various modifications and variations are possible without departing from the spirit and scope of the invention. Accordingly, claims are attached to disclose the scope of the invention. [Explanation of Symbols]

[0114] 100...Image reading device, 119...CIS, 120...White reference plate, 211...Memory, 201...CPU

Claims

1. A reading means comprising an image sensor for reading a document, a light source for illuminating the document with illumination light, and a rod lens array for focusing reflected light from the document onto the image sensor, A reference color plate is positioned opposite the reading means, A storage means that stores the reference color data obtained by reading the reference color plate with the reading means when no foreign matter is attached to the reference color plate, as comparison data, A detection means for detecting foreign objects based on reference color data obtained by reading the reference color plate with the reading means before reading the aforementioned document, and the comparison data, A filter that applies a filter processing corresponding to the periodic characteristics derived from the rod lens array to the input value to obtain an output value and outputs the said output value, It has, The detection means is an image reading device that detects the foreign object based on the reference color data to which the filtering process has been applied and the comparison data to which the filtering process has been applied.

2. The image reading device according to claim 1, wherein the detection means obtains the difference or ratio between the reference color data to which the filtering process has been applied and the comparison data to which the filtering process has been applied as a comparison result, and detects the foreign object based on the comparison result.

3. A reading means comprising an image sensor for reading a document, a light source for illuminating the document with illumination light, and a rod lens array for focusing reflected light from the document onto the image sensor, A reference color plate is positioned opposite the reading means, A storage means that stores in advance as comparison data the reference color data obtained by reading the reference color plate with the reading means when no foreign matter is attached to the reference color plate, An acquisition means for obtaining the difference or ratio between the reference color data obtained by reading the reference color plate with the reading means before reading the aforementioned document and the comparison data as a comparison result, A filter that applies filtering according to the periodic characteristics derived from the rod lens array, using the above comparison result as an input value, A detection means for detecting the foreign object using the comparison result to which the filtering process has been applied, An image reading device having [a certain feature].

4. The image reading device according to claim 1 or 3, wherein the filter is configured to perform a moving average on M input values ​​input to the filter to obtain an output value and output the said output value, and the M values ​​are integers or multiples of the period derived from the rod lens array that are closest to the said period.

5. The image reading device according to claim 4, wherein the period is a period corresponding to the pitch between adjacent rod lenses in the rod lens array.

6. The image reading device according to claim 1 or 3, wherein the comparison data is reference color data acquired by the reading means when there is no foreign matter in the optical path from the reference color plate to the image sensor.

7. The image reading device according to claim 2 or 3, wherein the detection means detects the foreign object based on the comparison result and a threshold.

8. The image reading device according to claim 7, further comprising a determination means for determining the threshold based on the brightness values ​​of N pixels surrounding the pixel of interest that is the basis for the comparison result.

9. The image reading device according to claim 8, wherein the determination means determines the threshold so that it is smaller than the average value of the brightness values ​​of the N pixels.

10. The image reading device according to claim 9, wherein the determination means determines the threshold by multiplying the average value of the brightness values ​​of the N pixels by a magnification less than 1.

11. The image reading device according to claim 9, wherein the determination means determines the threshold by subtracting a margin from the average value of the brightness values ​​of the N pixels.

12. A correction means for correcting the reference color data according to the detection result of the detection means, A holding means for holding a correction coefficient for shading correction determined based on the reference color data corrected by the correction means, A correction means for correcting the image data of the original document acquired by the reading means using the correction coefficient, The image reading device according to claim 1 or 3, further comprising the above.

13. The image reading device according to claim 12, wherein the correction means corrects or interpolates the image data of the pixels in the reference color data where the foreign object has been detected using image data of a plurality of pixels in the reference color data where the foreign object has not been detected.

14. The image reading device according to claim 13, wherein the plurality of pixels include at least two pixels located around the pixel in which the foreign object was detected.

15. A reading means comprising an image sensor for reading a document, a light source for illuminating the document with illumination light, and a rod lens array for focusing reflected light from the document onto the image sensor, A reference color plate is positioned opposite the reading means, A storage means that stores in advance as comparison data the reference color data obtained by reading the reference color plate with the reading means when no foreign matter is attached to the reference color plate, An acquisition means for obtaining the difference or ratio between the reference color data obtained by reading the reference color plate with the reading means before reading the aforementioned document and the comparison data as a comparison result, A detection means for detecting the foreign object using the comparison results, A filter that takes the comparison result as an input value, applies a filter processing corresponding to the periodic characteristics derived from the rod lens array to obtain an output value, and supplies the output value to the detection means, or takes the reference color data and the comparison data as input values, applies the filter processing to obtain an output value, and supplies the output value to the acquisition means, An image reading device having [a certain feature].

16. An image reading device according to any one of claims 1, 3, and 15, An image forming means for forming an image on a sheet based on image data generated by the image reading device, An image forming apparatus, including one.

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