JP2005260725A - Image evaluating apparatus, and image forming apparatus having image evaluating function - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To objectively evaluate about an image formed on a medium by an image forming apparatus. <P>SOLUTION: An image formed on a medium by an image forming unit is read at a position behind a fixing device by a CIS (Contact Image Sensor) 50. The read data is passed to an image analysis unit 92, and an analysis region having the conveyance direction as its short side and the longitudinal direction of the CIS as its long side is taken out. The image analysis unit 92 computes an average value of a value of pixels located in a line along the short side for pixels in the analysis region, and constructs an average value sequence (image information table). The image analysis unit 92 applies wavelet transformation to the average value sequence, and multiplies the result by a VIF (Visual Transfer Function). A maximum value Wmax, its position bmax, its period amax, and an average value Wave are determined from values obtained as the result. The statistical values obtained in this way are read by a control device board 301, and are displayed on a display unit 90. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to, for example, an image evaluation apparatus that analyzes data formed on a medium such as paper with a color material such as ink or toner and provides data for inspecting the image forming apparatus that has formed the image. The present invention relates to an image forming apparatus such as a printer having a function provided by the image evaluation apparatus.

  Conventional image forming apparatuses (printers, copiers, etc.) are provided with a test print mode in which an image signal provided in advance or an image creation program is operated to form a necessary image as a test print image. There is something. The test print image is generally a uniform solid image, especially a uniform halftone image, together with a character image and a color confirmation image. A uniform halftone image is easily affected by minute fluctuations in the image forming apparatus, and is a simple image for grasping the detailed operation state of the image forming apparatus. The user or service person can evaluate the output image of the image forming apparatus by referring to the test print formed on the medium and visually judging the blur or unevenness generated in the halftone image, In some cases, it is possible to estimate the cause of the abnormal state. In this case, the service person or the user evaluates the formed image, manipulates various parameters of the image forming apparatus that are estimated to be the cause of the abnormality, or repairs the defective portion so that the image forming apparatus is in an appropriate state or preference. It can be adjusted to the state. Note that unevenness is a state in which a density gradient of the image density that should be uniform is generated, and a streak is a linear image in which the density gradient of the change portion of the density is steep. Refers to a state that is deviated from a desired position.

  In addition, an image reading unit provided on the downstream side of the image fixing unit in the image forming apparatus, or a test print image recorded on a medium by an image scanner provided in the case of a copying machine or the like, An image forming apparatus that can read a toner image on a photosensitive drum and grasp the state based on the read result has been proposed. In such an image forming apparatus, the blur or unevenness of the test print image is detected from the image read by the image reading unit. Detection is based on frequency characteristics obtained from the read image data, that is, the average value and standard deviation of the luminance, density, or color component, or by applying Fourier transform to the read image data. Methods have been proposed for judging tumble and unevenness.

Furthermore, instead of the Fourier transform, the read image data is subjected to a certain number of wavelet transforms in the width direction and the length direction, so that a low-pass component including all components in a region coarser than a certain size is obtained. There has also been proposed a technique for obtaining a correction coefficient for correction to be performed on image data in order to make the density unevenness of the obtained low-pass component uniform (see Patent Document 1, etc.). In the wavelet transform, the degree of similarity between the original signal waveform and the mother wavelet is obtained by calculating the correlation between the basic waveform (hereinafter referred to as the mother wavelet) and the original signal waveform. In the wavelet transform, since the conversion result is given by using the period and position of the mother wavelet included in the original signal waveform as parameters, the frequency characteristics at a certain position can be extracted.
JP 2000-244740 A

  By the way, when the user or service person visually evaluates the test print image, the evaluation result may not be immediately reflected in the state of the image forming apparatus because the user or service person manually evaluates the image. In addition, know-how is required to evaluate the quality of an image or to estimate the cause of an abnormality of an image forming apparatus from an image formed on a medium, and it is difficult to acquire an evaluation technique overnight. Therefore, there is a case where the evaluation is not appropriate, and there is a problem that it is difficult to operate the parameters of the image forming apparatus based on the inappropriate evaluation and set them to an appropriate state.

  Further, in the method of applying the Fourier analysis to the image data read using the image reading unit described above, the evaluation is greatly affected by the overall inclination in the image, and the thin unevenness or the thick unevenness. There is a drawback that it is not known at all whether it is sharp or blurry. I couldn't know where the spot was uneven without using another search method.

  In addition, in the method using Fourier analysis, it is possible to discriminate thin unevenness and thick unevenness, or sharp unevenness and blurred unevenness as periodic components of the entire image, but detection of periodic components of the entire image is possible. Due to the essential characteristics of the Fourier transform method, there has been a problem that single or sporadic blurs, irregularities, etc. cannot be detected correctly. The essential characteristics of the Fourier transform are the fact that the Fourier transform is caused by treating the target signal waveform as a sine wave synthesis, and since the position information is lost, information such as where the unevenness in the image is It could not be detected from the Fourier coefficient.

  Further, a technique for obtaining a correction coefficient for correction to be performed on image data by performing wavelet transform on the read image data is to detect features and adjust the image data to correct the image. Although proposed, this is a technique that corrects only components that are coarser than a certain size at a certain position, and has not evaluated image wrinkles that the user can visually recognize, such as unevenness, blurring, and streaks. In addition, even if image defects caused by mechanical problems can be resolved by correcting the image data, they cannot be resolved as the root cause, and the user is not aware of the problem, making the problem even more difficult. There is also a risk of seriousness.

  The present invention has been made in view of the above-described conventional example, and image data obtained by reading an image formed on a medium by an image forming apparatus does not depend on human subjective evaluation, and is particularly visual. An object of the present invention is to provide an image evaluation apparatus and an image forming apparatus capable of objectively evaluating a portion that is easy to appeal to.

  The present invention has been made in view of the above conventional example, and has the following configuration.

An image evaluation apparatus for evaluating the quality of an image formed by a color material on a medium,
Input means for inputting an image formed on the medium;
Wavelet conversion means for performing wavelet conversion on the image information;
Visual characteristic conversion means for further applying weighting conversion according to visual frequency characteristics for the coefficient value converted by the wavelet conversion means;
Statistical processing means for statistically processing the coefficient value converted by the visual characteristic conversion means;
Output means for outputting a statistical value processed by the statistical processing means.

Alternatively, image forming means for forming an image with a color material on a medium;
An input unit for inputting an image formed on the medium for evaluating an image formed on the medium by the image forming unit;
Wavelet conversion means for performing wavelet conversion on the image information, visual characteristic conversion means for further applying weighting conversion according to visual frequency characteristics for the coefficient value converted by the wavelet conversion means, and the visual An image evaluation apparatus comprising: statistical processing means for statistically processing the coefficient values converted by the characteristic conversion means; and output means for outputting the statistical values processed by the statistical processing means.

  As a result, the present invention objectively relates to image data obtained by reading an image formed on a medium by an image forming apparatus, particularly on a portion that is easily appealed visually, without depending on human subjective evaluation. It is possible to evaluate.

  In particular, among the disturbances such as unevenness, blurring, or streaks that appear in the image, the frequency components that appeal to human vision, for example, by generating and evaluating statistical values indicating the characteristics and position of the image, etc. It is possible to provide a material for objectively specifying the amount and position of the disturbance of an image that tends to stay and the cause thereof. For this reason, it is possible not only to easily deal with the disturbance of the image but also to deal with the root cause.

  Further, for image data obtained by reading an image formed on a medium, the read luminance information is converted into density information, and after reduction conversion, a plurality of features are provided as statistical values indicating the features appearing in the image data. By taking out the target points so as not to overlap and taking the average of them, analysis closer to visual observation became possible.

  Further, by analyzing the features of the image for each color component, it is possible to analyze the features that are easily visually recognized with respect to the color information.

  Furthermore, a blurring effect can be given by performing filtering processing such as averaging on the image information, and features that are easier to visually recognize can be analyzed.

  Furthermore, by using a low-order mother wavelet and a high-order mother wavelet together as the mother wavelet used for wavelet transformation, it is possible to determine whether the periodicity of features appearing in the image is high or low. It was.

  In addition, when the feature in the image has periodicity, the pitch unique to the corresponding image forming apparatus can be searched, and in other cases, the abnormal factor location can be estimated based on the magnitude of the cycle. Therefore, feedback control such as changing the setting conditions of the image forming apparatus as a subsequent action is also possible.

[First Embodiment]
<Configuration of image forming apparatus>
FIG. 2 is a diagram illustrating an image forming apparatus according to the present invention. The image forming apparatus includes a reader scanner unit 1 and a printer unit 20. The reader scanner unit 1 scans a document placed on the platen glass 2 and the pressure plate 3 with a fluorescent lamp 4 and a reflection mirror 5, and reflects reflected light from the document with reflection mirrors 6, 7 and 8. It passes through the lens 9 and is converted into a digital image signal by the CCD 10.

  On the other hand, the digital image signal read by the CCD 10 is converted into an image signal to drive the semiconductor laser 21 in the printer unit 20 through filter processing, density conversion, γ conversion, and the like by an image processing device (not shown). The laser beam generated by the semiconductor laser 21 is irradiated to the photosensitive drum 26 through the lens 24 and the reflection mirror 25 by the rotation of the polygon motor 22 and the polygon mirror 23. In this image forming apparatus, the resolution in the sub-scanning direction is 600 dpi (dots / inch), and the basic resolution in the main scanning direction is also 600 dpi. Regarding the main scanning direction, the resolution can be changed as long as the lighting cycle is changed, but the same in the main and sub scanning directions.

  The photosensitive drum 26 is previously charged with a uniform potential by a primary charger 27, and an electrostatic latent image corresponding to image information is formed by scanning with a laser beam. The potential of the electrostatic latent image is detected by the potential sensor 28 and can be changed by adjusting the discharge current value in the primary charger 27 and the intensity of the laser beam. The electrostatic latent image on the photosensitive drum 26 is visualized as a toner image by toner from the developing device 29. This toner image is subjected to corona discharge from the post charger 30 on the photosensitive drum and the charge amount is adjusted, and then transferred by the transfer charger 31 and the separation charger 32 from the paper feed deck 33. Transferred to the paper 34. Thereafter, the transfer paper 34 is moved by the conveying belt 35, and the toner image is fixed on the transfer paper in the fixing device 36.

  A contact image sensor (hereinafter referred to as CIS) 50 is disposed on the downstream side of the fixing device 36 and between the conveyance roller pairs 37 and 38, and an image after fixing is electronically read with a luminance component.

  The transfer residual toner remaining without being transferred onto the transfer paper at the position of the transfer charger 31 is peeled off from the photosensitive drum by the cleaner 37, and the residual potential on the photosensitive drum is made uniform by the static eliminator 38. Ready for image formation.

  FIG. 3 is a diagram illustrating the electrical configuration of the control board and the external input / output device inside the image forming apparatus. In the figure, a ROM 70 in which a control program is described and a RAM 71 for developing image signals are connected to a CPU 72 as well as a temporary storage element for necessary data on the program. In addition, the interface element I / O 73 and the data conversion elements A / D converter 74 and D / A converter 75 are connected to an external input / output device, and information is input between the control board and the input / output device. Is output. The reader scanner unit 1 and the CIS device 50 are connected as an image input unit in the present invention. Image data (image information) read by the CIS 50 is input to the image analysis unit 91 via the control board 301. Of course, it is also possible to input image data read by the reader scanner unit 1 to the image analysis unit 91 instead of the CIS 50.

  Further, a display unit 90 that displays the state of the image forming apparatus, an image analysis unit 91 that determines the state of the image in the present invention, and various control units 92 that control each unit of the image forming apparatus are connected. Here, the image analysis unit 91 may include the configuration shown in the figure with dedicated hardware, or may be configured with a CPU, a memory, and an interface circuit for connecting to the bus, like the control board 301 of FIG. May be. In this case, the image analysis unit 91 is realized by executing a program of the procedure shown in FIG. 7 for image analysis. In any case, the image analysis unit 91 includes a memory 910 for storing image data to be analyzed, image data being analyzed, or result data. In other embodiments, the program of the procedure of FIG. 10 and FIG. 13 described there is executed. It can also be realized by executing a predetermined program on the control board 301.

  FIG. 4 is a cross-sectional view for explaining the CIS 50. In a region surrounded by the pair of conveyance rollers 37 and 38, the CIS 50 is arranged so as to form a gap G with the counter plate 51. When the transfer paper discharged from the fixing roller passes through the gap G, the CIS 50 detects the toner image on the transfer paper. Inside the CIS 50 are an LED array 60 that illuminates the toner image on the transfer paper, a contact glass 61 that protects the interior from paper rubbing and paper dust, a selfock glass 62 that guides the projected light flux from the transfer paper, and a projection A photodiode 63 for reading as an image is incorporated. This CIS is a high-definition sensor having a longitudinal direction of about 300 mm and a longitudinal resolution of 2400 dpi, and the resolution in the paper passing direction inside this image forming apparatus is 2400 dpi. In addition, since the CIS 50 is obtained as luminance signal information of 8 bits and 256 gradations, it is possible to make a precise determination of gradation. FIG. 5 is a top view for explaining the CIS 50. It is shown that the CIS 50 is disposed on the counter plate 51 in a region surrounded by the conveyance roller pairs 37 and 38.

<Configuration and operation of image analysis unit>
FIG. 1 is a block diagram of an image analysis unit 91 that determines the state of an image according to the present invention. The image information read by the CIS 50 is input to the image analysis unit 91 and the preprocessing unit 100 processes the image. In the present embodiment, the pre-processing unit 100 saves, in a storage unit (not shown) included in the image analysis unit 91, only the range to be analyzed (hereinafter referred to as an analysis range) from the two-dimensional luminance information read by the CIS 50. . In addition, since it is not necessary to calculate two-dimensionally in order to detect blurring, unevenness, etc., the read image is divided into areas in the transfer paper transport direction or the longitudinal direction of the photoconductor, etc. The pixel values arranged in the short side direction of the range are averaged to obtain one-dimensional information arranged in the long side direction. Therefore, in the present embodiment, the analysis range is a rectangular range in which the longitudinal direction of the photosensitive member or the like is the long side and the transport direction is the short side. Specifically, the analysis range is a range in which the short side along the conveyance direction is 5 mm and the long side along the longitudinal direction of the CIS is 300 mm. The reason why the long side is set to 300 mm is that, in the present embodiment, it is assumed that the medium to be evaluated is A4 size and the transport direction is the direction along the short side. Of course, it is desirable to change the length of the long side according to the paper size. In the present embodiment, the position of the analysis range is, for example, near the center of the medium in the transport direction. Of course, other positions are also acceptable.

  The pre-processing unit 100 obtains an average value for each pixel row arranged in the short side direction for the image data in the analysis range at a fixed position in the entire image data, and averages the number corresponding to the number of read pixels in the long side direction. The arrangement of pixel values is stored in the storage unit as an image information table. The image information table read at 2400 dpi for a length of 300 mm is an array of average luminance data for approximately 28400 pixels.

  The wavelet transform unit 101 performs wavelet transform on the image information table (a sequence of average luminance data) generated by the preprocessing unit 100. The wavelet transform is a function of the position of the original signal and the period of the mother wavelet, that is, how much a basic waveform signal called a mother wavelet is included in the signal to be analyzed (hereinafter referred to as the original signal). Is a signal processing method calculated as follows. In the present invention, a general Morlet mother wavelet is used. The mother wavelet Ψ (x) is given by the following calculation formula (Formula 1).

Here, x indicates the position of the mother wavelet, a indicates the waveform period, and σ indicates the number of waves. In this embodiment, σ = 1.0, which is the simplest mother weblet. Since the mother wavelet Ψ (x) includes a term of the Gaussian function exp (−x ² ), even if the position x is changed, it is a finite function. This is because if the position x is sufficiently large, the mother wavelet Ψ (x) becomes almost zero. Therefore, when compared with the signal waveform of the original signal, the waveform is smaller in the length x direction.
What indicates how much this mother wavelet is included in the signal waveform of the original signal, in other words, what calculates the cross-correlation with the mother wavelet is the result of the wavelet transform. Given. In the present embodiment, the coefficient obtained as a result of the wavelet transform may be simply referred to as wavelet transform.

Here, f (x) is a signal waveform of the original signal, and in this embodiment, is an image information table, that is, an array of average luminance data. In the formula, a indicates the period of the waveform, and b has the same meaning as the position x and indicates a specific position in the signal. Although the wavelet transform unit 101 performs computation with a predetermined periodic pitch in order to perform digital computation processing, Equation 2 is a continuous wavelet transform, not a discrete wavelet transform. The continuous wavelet is disadvantageous in that the processing time is longer than that of the discrete wavelet transform, but it is advantageous in evaluation accuracy because the resolution of the obtained transform result is high. The continuous wavelet transform is generally known as a numerical solution, and can be solved using this solution.
Here, the VTF conversion unit 102 performs weighting conversion on the obtained two-dimensional wavelet transform with the period a and the position b. VTF (Visual Transfer Function) indicates a visual frequency characteristic, and is represented by a value of 0 to 100% (0 to 1). Weighting based on human sensitivity is performed on wavelet transform by VTF transform. FIG. 18 shows an example of conversion characteristics of a VTF conversion table used for conversion by the VTF conversion unit 102 in the present embodiment. In the present embodiment, the visibility in the viewing environment at a distance of 30 cm is registered in the VTF conversion table as VTF. An operation is performed to take the product of the obtained wavelet transform result and the entry in the VTF transform table. Multiplication is performed for each corresponding period. That is, the result (coefficient) of the wavelet transform is obtained using the period and position as parameters. Then, for a certain period, for each position (the position can be given in units of pixels), the coefficient value of that period is multiplied by VTF (0 to 1) of that period. This is repeated for all cycles. Even in the case of continuous wavelet transform, the result is given in discrete cycles in actual calculation, and therefore, it may be repeated for all the calculated cycles. The calculation result of the VTF conversion is stored in the storage unit of the image analysis unit 91. The value obtained in this way is a value that is weighted to increase the weight for the coefficient of the period that is easy to visually recognize and decrease the weight for the coefficient of the period that is difficult to visually recognize.

  The VTF is given as a parameter in the period in the conversion characteristics of FIG. For example, a striped pattern with a certain period is drawn on paper or the like, and a human observes it from a position 30 cm apart. In this case, the degree that the observer can recognize is indicated as VTF. In the example of FIG. 18, it can be recognized that a striped pattern with a certain period can be recognized by 100%, but the recognition rate of a striped pattern with a period before and after that period decreases. Of course, FIG. 18 is only an example. For example, VTF conversion is possible in which 100% is visible from a direct current (uniform luminance) component to a striped pattern of a certain period, and the recognition rate of a striped pattern having a period shorter than that period gradually decreases. A table may also be employed. Of course, it is desirable that the period that is a parameter of the VTF conversion table coincides with the period calculated by the wavelet conversion.

  Thereafter, the statistical processing unit 103 derives a numerical value specific to the analysis target image from the analysis result subjected to the VTF conversion. In the present embodiment, the maximum value Wmax, the position bmax indicating the maximum value Wmax, the period amax, and the average value Wave are obtained. The maximum value Wmax is the maximum value among all the coefficient values obtained after VTF conversion, and the position bmax and the period amax indicating the maximum value Wmax are the position b and the period a that give the maximum value Wmax, and the average The value Wave is an average value of all coefficients.

  Ideally, all the pixels to be analyzed have the same luminance. In an image forming apparatus that performs pseudo-gradation processing, the spatial frequency included in an image includes a direct current component (in practice, the maximum period of the spatial frequency is determined by the length of the pixel column of the image information table, so the direct current period is finite). In addition, a component having a period corresponding to the arrangement of the threshold matrix used for the pseudo gradation processing is included. Therefore, a wavelet having a direct current (that is, maximum period) wavelet at any position of the original signal and a wavelet having a period corresponding to the period of the threshold matrix for binarization processing has a non-zero coefficient, and the other waves The let coefficient should be zero.

  In an image forming apparatus capable of multi-value recording according to the density level of image data, ideally, only a direct current component is included in the spatial frequency included in the image. Therefore, any position of the original signal should have a non-zero coefficient for a direct current (ie, maximum period) wavelet, and the other wavelet coefficients should be zero.

  Therefore, the average value Wave represents a deviation from the ideal image as the entire image. The maximum value Wmax indicates the degree of luminance most deviated from the average value (or ideal value), and the position bmax and the period amax indicate the position and period most deviated from each other. From these statistical values, the operator can specify the position where the most characteristic part such as displacement and unevenness on the image is located in the direction orthogonal to the scanning direction, and specify the degree. it can. Since these statistical values have been subjected to VTF conversion, periodic components (frequency components) that are difficult to visually recognize or cannot be visually recognized are not extracted as image features.

<Specific procedure for image evaluation>
FIG. 6 is a flowchart for test printing. This flowchart is executed by the CPU 72 of the control board 301. First, image data of a uniform halftone image of the entire paper size is developed on the RAM (s1). The semiconductor laser is driven in accordance with the image data to execute test printing (s2). Note that the paper size is that of the transfer paper currently mounted on the paper feed deck 33, but if there are transfer papers in a plurality of paper feed decks, an arbitrary paper feed deck or paper feed deck is selected. It may be. Thus, the image formed on the medium becomes the object of evaluation.

  FIG. 7 is a flowchart of a routine for performing image analysis in the present embodiment. The procedure in FIG. 7 is executed by the image analysis unit 91. Steps m1 and m2 are executed by the preprocessing unit 100, step m3 is executed by the wavelet conversion unit 101, step m4 is executed by the VTF conversion unit 102, and steps m5 to m8 are executed by the statistical processing unit 103. However, when the image analysis unit 91 is realized by a CPU and a memory, the procedure of FIG. 7 is executed by the CPU of the image analysis unit 91.

  First, as shown in FIG. 1, the analysis range is extracted from the two-dimensional luminance information read by the CIS 50 by the preprocessing unit 100 and stored (m1). Further, the pre-processing unit 100 calculates an average value of the pixel columns in the short side direction and converts it into a one-dimensional image information table (average luminance data string) (m2).

  Next, the wavelet transform unit 101 performs wavelet transform on the image information table (m3). The VTF conversion unit 102 calculates the product of the wavelet conversion result and the VTF for each period (m4). This adds to the visual impact.

  The statistical processing unit 103 compares all the coefficients obtained in step m4 to obtain the maximum value Wmax (m5), stores the position bmax and period amax of the maximum value in the storage unit (m6), and further analyzes the coefficient of the analysis result Is obtained and stored in the storage unit (m7).

  Thereafter, the obtained maximum value Wmax, the position bmax, the period amax, and the average value Wave are passed to the control board 301. The CPU 72 of the control board 301 reads these values and displays them on the display unit (m8). Of course, you may print. The display method may not only display the statistical values, but may issue a warning requesting confirmation within the image forming apparatus if the statistical values Wmax and Wave are equal to or greater than a predetermined value. In this case, the average value Wave is the evaluation result of the entire image, and the maximum value Wmax is the most conspicuous, uneven, or streaked. From these analysis results, the user or service person can evaluate the image without subjective evaluation.

  FIG. 8 is a diagram for explaining an example of a conversion value obtained by image analysis in the present embodiment. An example of image data in the analysis range from the top (a), a diagram of luminance distribution in the image information table (b), an example of coefficients after wavelet conversion (c), and an example of coefficients after VTF conversion (d). In (a), the luminance is represented by the density of the image. In (c) and (d), the coefficient value is expressed as a concentration. However, the density and the coefficient value do not correspond one-to-one. Whereas the representation of the graph is limited to 256 levels, the coefficient value has more than 256 levels, so when the coefficient value increases (or decreases), the corresponding concentration does not saturate and cyclically. expressed. For example, as the coefficient value increases, the color representing the color changes from white to black, and when the coefficient value further increases and the density is saturated, the color representing the coefficient value returns to white. FIG. 8C is expressed as such.

In the image analysis, the two-dimensional read image in FIG. 8A is first averaged in the short side direction to obtain one-dimensional data in FIG. By performing wavelet transform on this one-dimensional data, post-wavelet-transformed data W (a, b) at position b and period a shown in FIG. 8C is obtained. By performing VTF conversion on this, post-VTF converted data W _VTF (a, b) at position b and period a shown in FIG. 8D is obtained. By calculating the maximum value Wmax, the position bmax, the period amax, and the average value Wave from the VTF-converted data W _VTF (a, b), it is possible to extract the features of the read image. Of course, FIG. 8 is only an example showing that such a result can be obtained.

  As described above, the continuous wavelet transformation is performed on the image data, and the VTF transformation using the VTF can be directly applied to the obtained transformation value. For this reason, the result of continuous wavelet transformation can be weighted by the visual frequency characteristic indicated by VTF, and the visual feature can be extracted together with its position.

<Modification>
Note that the present invention is also applicable to an image forming apparatus provided with only one of the reader scanner unit 1 and the CIS 50. Even if neither the reader scanner unit 1 nor the CIS 50 is provided, an image formed on a medium can be read by another image scanner, and evaluation can be performed based on image data obtained from the scanner. . In this case, the evaluation can also be performed by causing the general-purpose computer to execute the procedure shown in FIG. 7 instead of the image forming apparatus.

  In the present embodiment, image defects (such as unevenness and blurring) are analyzed and evaluated in the direction orthogonal to the conveyance direction of the image forming apparatus. The analysis range (300 mm × 50 mm) defined in the present embodiment is defined in this way because the paper size is A4 and the transport direction is the direction along the short side direction. Therefore, when the present embodiment is applied to other sizes, it is necessary to determine the analysis range so that the short side direction of the analysis range becomes the transport direction during image formation of the medium to be evaluated. Therefore, when the image is read from the medium conveyed in the conveyance direction at the time of image formation as in the present embodiment, the dimensions of the analysis range need only be changed to the medium size. However, when an image is read regardless of the conveyance direction at the time of image formation, for example, when an image is read using the reader scanner 1 or when an image is read by an externally connected image scanner, the The size is preferably entered separately as information. The input may be performed manually by an operator on an operation panel provided in the image forming apparatus according to the present embodiment, for example. Further, when an image is read using the reader scanner 1 that is integrally attached to the image forming apparatus, if the medium size is also detected simultaneously with the reading, the detected size may be input simultaneously. .

  Further, if the image is evaluated by a general-purpose computer, it is necessary to separately input the transport direction at the time of image formation. In that case, the size and transport direction of the medium are also input. Then, the image data in the analysis range in which the designated conveyance direction is the short side and the direction orthogonal to the short side is the long side is evaluated according to the procedure shown in FIG.

  When an image formed by a color printer is evaluated, a uniform halftone image is recorded on the medium for each color component of the color material used by the color printer, and the procedure of this embodiment (of course, other implementations are performed). It can be evaluated for each color component).

[Second Embodiment]
FIG. 9 shows a block diagram of the preprocessing unit 100 in the present embodiment. In the present embodiment, the configuration is the same as that of the first embodiment except for the preprocessing unit. In FIG. 9, the range storage unit 110 stores only the analysis range from the two-dimensional luminance information read by the CIS 50. The range storage unit may be the storage unit described in the first embodiment. The brightness data is converted into density data by a density conversion unit 111 using a table representing the correlation between brightness and density unique to the CIS 50. This conversion can also be performed by a procedure of converting to a standard luminance space in which the characteristic unique to CIS is corrected, and then converting it to density. The former is realized by a general image scanner using CIS. The latter is realized by a printer that converts luminance into density. The density data thus obtained is reduced to 1/16 by the reduction unit 112. The reduction is performed by thinning out pixels, for example. Thereafter, the one-dimensional conversion unit 113 averages the direction on the short side to create one-dimensional information, that is, an image information table to be analyzed.

  Also in this embodiment, for image analysis in the longitudinal direction of the photoconductor or the like, information on the conveyance direction 5 mm which is the short side and the information on the longitudinal direction 300 mm which is the long side is obtained and an average value for the short side direction 5 mm is obtained. This is stored as one-dimensional information (similar to the image information table of the first embodiment). The image information table read at 2400 dpi over a length of 300 mm has been converted to 1/16 of the density data by the preprocessing unit 100, and thus becomes one-dimensional average density data for approximately 1780 pixels. In addition, since the number of pixels of the one-dimensional data to be analyzed is reduced, there is an advantage that the calculation load of the wavelet transform unit is reduced. At this time, a reduction ratio that does not cause moiré with the image processing of the output halftone image is important. When there are a plurality of halftone image lines (for example, when the threshold matrix size can be selected from a plurality of matrix sizes), a reduction ratio corresponding to the number of lines should be selected.

  FIG. 10 is a flowchart of a routine for performing image analysis in the present embodiment. FIG. 10 is also executed by the image analysis unit 91. FIG. 11 shows an example of data processed by the procedure of FIG.

First, as shown in FIG. 9, the analysis range is stored from the two-dimensional luminance information read by the pre-processing unit 100 using the CIS 50 (n1). Further, the pre-processing unit 100 converts the density into the density and averages in the short side direction, converts it into one-dimensional average density data, and stores it in the memory as an image information table (n2). Next, the wavelet transform unit 101 applies wavelet transform to the image information table and stores the value (n3). Then, in the VTF conversion unit 102, the product of the stored wavelet conversion result and the VTF is taken, and the influence on the vision is added (n4). FIG. 11A shows VTF-converted data W _VTF (a, b).

  Then, the statistical processing unit 103 obtains the maximum value Wmax (n5), and stores the position bmax and the period amax of the maximum value Wmax (n6).

Furthermore, in this embodiment, instead of the average value of the analysis result, a certain maximum value is selected from the large value from the coefficient value group after the VTF conversion, and the average value Wz is obtained and stored (n7). The maximum value (peak) Wm is W _1D (b−1) ≦ W _1D (b)> W _1D (b + 1) or W _1D (b−1) <W _1D (b) ≧ W _1D (b + 1). It is defined that W _1D (b) is satisfied. However, when selecting the local maximum value here, the local maximum value is not simply selected in the descending order, but as follows.

That is, in step n7, first, the maximum value at each position b is retrieved from the VTF-converted data W _VTF (a, b) (FIG. 11 (a)), and the maximum value at each position is configured. Then, a conversion value group W _1D (b) using the position as a parameter is created (FIG. 11B). FIG. 11B shows two parameters of position and frequency. Since the maximum frequency at each position is uniquely determined, it is actually a function of one parameter.

Next, a value Wm having a maximum value is searched from W _1D (b) and stored. An example of the searched local maximum value is shown as a circle in FIG. The subscript number m of Wm indicates each of 1 to m maximum values. Since the local maximum value Wm is a local maximum value with each period information a, the range of the period a is centered on the position b of the local maximum value, and a plurality of local maximum values are included therein. The maximum maximum value among them is regarded as a maximum value representing the range, and the other maximum values are discarded. Then, a certain number of local maximum values are selected from the top in the order of size from the remaining local maximum value groups (circles in FIG. 11D), and the average value Wz is obtained.

The specific procedure is as follows, for example.
(1) For example, from the stored maximum value series W _1D (b) at each position, a maximum value Wm satisfying the above definition is retrieved and stored in the storage unit of the image analysis unit 91. The local maximum value stored here is called a set of local maximum values.
(2) First, the maximum maximum value W1 is selected from the set of maximum values, and the position b and the period a together with the value are stored in the storage unit of the image analysis unit 91.
(3) The local maximum value within the range of the period a1 of the local maximum value W1 centered on the position b1 of the selected local maximum value W1 is searched from the set of stored local maximum values and deleted.
(4) Repeat from (2) to select the maximum maximum from the set of remaining maximums. However, what is selected is not the maximum value W1, but the maximum value in the order corresponding to the number of repetitions, such as W2, W3. The end condition is that the processing of (2) is completed for m maximum values, or the set of maximum values is empty.

  If m maximum values W1 to Wm are stored in this way, the average value Wz is calculated. Step n7 is executed as described above.

  Thereafter, the obtained maximum value Wmax, its position bmax, the period amax and the average value Wz of the maximum values are read out by the CPU in the control board and displayed on the display unit (n8). Further, in step n9, the maximum value Wmax and the average value Wz of the maximum values are compared. For example, if one is twice or more of the other, one-time unevenness occurs, and if not, multiple unevenness and blurring are generated. A message indicating whether the resulting unevenness is single or plural is displayed.

  Here, the average value Wz of a certain number of local maximum values means an average value of conspicuous unevenness. As an index indicating unevenness, a certain number of pixels having a maximum density (or luminance) may be simply taken out of the two-dimensional analysis data and averaged. However, the inventors of the present invention select a sample for obtaining an average value by a method of selecting the next maximum value by excluding the maximum value at the position included in the range of the period a from the position b of the maximum value. Thus, the average value of a plurality of noticeable unevenness is obtained. The reason for this is that when a certain number of local maximum values are extracted in the order of the size of the two-dimensional analysis data, small irregularities are concentrated in the vicinity of the noticeable unevenness, and as a result, only the values in the vicinity of the noticeable unevenness are collected. This is because the result may differ. In visual confirmation, it is easy to determine that there are a plurality of unevenness in different positions, and small unevenness in the vicinity of unevenness with large amplitude is difficult to focus on.

  According to such an averaging process of the present embodiment, as in the case of observing an image by visual observation, some noticeable unevenness is considered from the first unevenness and is in the vicinity of unevenness with a large amplitude. By eliminating another unevenness with a small amplitude, a calculation close to visual observation is possible.

  It is also possible to perform analysis by converting the read luminance information into density information and reducing and then performing wavelet transform and VTF transform. By taking the average, analysis close to visual observation is possible.

[Third Embodiment]
In this embodiment, the CIS 50 in the first and second embodiments is not used, and a method of detecting this by the reader scanner unit 1 attached to the image forming apparatus shown in FIG. 1 is adopted. In this embodiment, the reader scanner unit 1 can read an image in full color such as RGB. The same method as the method of reading the image using the reader scanner unit 1 for a normal copy image by placing the test print output by the user or service person on the platen glass 2 of the reader scanner unit 1 Two-dimensional luminance information is obtained by reading the test printed transfer paper. However, since the basic resolution of the output test print is 600 dpi for each color and the basic resolution of the reader scanner unit 1 is 600 dpi for each color, moire may occur. Therefore, in the present embodiment, reading is performed with magnification of 400% in the scanning direction, and data for 2400 dpi is obtained in the scanning direction.

  FIG. 12 is a block diagram of the preprocessing unit 100 in the present embodiment. Other configurations are the same as those in the first or second embodiment. In FIG. 12, only the analysis range is stored from the two-dimensional image information read by the reader scanner unit 1 by the range storage unit 110. The image data is decomposed into a luminance component and a color component by the color conversion unit 121. Specifically, for example, the RGB color system read by the scanner is converted into an XYZ color system, an L * a * b * color system, an L * C * h * color system, or the like. The hue component is a two-dimensional value representing the hue and saturation, but in this embodiment, the hue is calculated. Of course, saturation may be performed. With respect to this hue component, the blurring unit 122 calculates the average value of the pixel of interest and 10 pixels before and after in the scanning direction. Thereafter, it is averaged by the one-dimensional conversion unit 113 to obtain one-dimensional information. In this embodiment, a filtering process is performed to calculate the average value of the hue components for 10 pixels before and after the target pixel in order to blur the image. You may have it. The one-dimensional information created in this way becomes the image information table in the first embodiment, which is the object of wavelet analysis. The preprocessing unit 100 performs the processes so far.

  In this embodiment, in order to perform image analysis in the conveyance direction of the medium on which the image is formed, for example, the longitudinal direction of the photoreceptor of the electrophotographic image forming apparatus is the short side, and the conveyance direction is the longitudinal direction. The range of is the analysis range. In the present embodiment, it is assumed that the scanning direction and the conveyance direction during image formation coincide with each other. Then, in the analysis range, the average value of the hue component of the pixel is obtained for each pixel column along the short side, and is stored as one-dimensional information in the longitudinal direction, that is, an image information table. An image information table of an image read at 2400 dpi is converted into one-dimensional average color data for approximately 39700 pixels by the preprocessing unit 100.

  FIG. 13 is a flowchart of a routine for performing image analysis in the present embodiment. This procedure is executed by the image analysis unit 92. As shown in FIG. 12, the analysis range is stored from the two-dimensional image information read by the reader scanner by the preprocessing unit 100 (p1). Further, the pre-processing unit 100 performs averaging in the short side direction to convert it into one-dimensional average color data (p2).

  Next, assuming that the number of waves of the mother wavelet represented by Equation 1 is 1.0, the wavelet transform unit 101 performs wavelet transform and stores the result (p3). Then, the VTF conversion unit 102 calculates the product of the wavelet conversion result and the VTF for each period, stores the result, and considers the effect on vision (p4).

  Then, the statistical processing unit 103 obtains the maximum value Wmax1 from the VTF converted count value (p5) and stores it together with the position bmax1 and the period amax1 of the maximum value (p6). In addition, an average value Wz1 for a certain number is obtained and stored in order from the value with the largest maximum (peak) value (p7). Here, the local maximum values may be simply selected in descending order. However, in the same manner as in the first embodiment, in the period range of the local maximum value, the maximum local value other than the maximum value may not be used as a sample.

  Furthermore, in this embodiment, the wavelet transform is performed by the wavelet transform unit 101 with the number of waves of the mother wavelet σ shown in Equation 1 being 4.0 (p8), and the VTF transform unit 102 performs the period between the wavelet transform result and the VTF. Each product is taken into consideration and the effect on vision is taken into account (p9). The statistical processing unit 103 obtains the maximum value Wmax2 (p10), and stores the position bmax2 and the period amax2 of the maximum value (p11). Further, an average value Wz2 for a certain number is calculated and stored in order from the largest local maximum (peak) value (p12). Steps p4 to p7 and steps p9 to p12 are the same as the processing procedure.

  Thereafter, two maximum values Wmax1 and Wmax2 obtained for different wave numbers, positions bmax1 and bmax2 of the respective maximum values, periods amax1 and amax2 of the respective maximum values, and high peak values corresponding to several from the top The two average values Wz1 and Wz2 are read from the storage unit of the analysis processing unit 92 by the CPU in the control board and displayed on the display unit (p13).

  If the number of waves σ is 1.0 and 4.0, the meanings of the results obtained for the other are different even if the other analysis conditions are the same. When σ is 1.0, it is suitable for detection of unevenness and blurring with a small periodicity, while when σ is 4.0, it is suitable for detection of unevenness and blurring with a relatively periodicity. That is, it can be seen from the difference in the value of σ whether or not defects appearing in the image are periodically generated. Therefore, the magnitudes of the maximum values Wmax1 and Wmax2 are compared (p14), and whether or not they are periodic is displayed by, for example, a message indicating that there is periodicity or no periodicity (p15). If Wmax1 is larger, it can be seen that the maximum value is unevenness or blurring with small periodicity, so a message indicating that the periodicity is small is displayed. At the same time, the location of unevenness in the image can be determined by bmax1, and the line width (the width of unevenness and blurring) can be determined to be approximately half of amax1, so the values of bmax1 and amax1 are also set together with the message. It is desirable to display. On the other hand, if Wmax2 is larger, it can be determined that there is periodicity, the position can be determined as bmax2, and the period can be determined as amax2. Therefore, it is desirable to display the values of bmax2 and amax2 together with a message indicating that there is periodicity.

  The average values Wz1 and Wz2 are compared (p16), and whether or not they are periodic is displayed by, for example, a message indicating that there is periodicity or no periodicity (p17). The periodicity may be determined not by the maximum value but by the average value. If Wz1 is larger, it can be seen that the average value is unevenness or blurring with a small periodicity. In addition, it can be seen that the line width average is approximately one half of the average of the period of each local maximum value which is a population set for calculating Wz1. Therefore, if Wz1 is larger, together with a message indicating that the periodicity is small, a half value of the average period of each local maximum value that is a population set for calculating Wz1 is calculated and displayed. You may do it.

  By analyzing the chromaticity as described above, it is possible to analyze the unevenness, blurring, and streaks of the image that appear as the difference in hue (or saturation) in the same manner as the luminance analysis. As a result, the user can objectively grasp the nature of the image defect on hue or saturation, and can take corrective action.

  In addition, by performing wavelet analysis on the same image using two different wavenumber mother wavelets, the analysis results are compared with each other, and the periodicity of defects appearing in the image is judged. It became possible to do. As a result, it is possible to more precisely cope with the malfunction of the image forming apparatus.

  The image information of the output image may be read by a document reading scanner, the color information can be analyzed, and the blurring effect may be given by performing filtering processing such as averaging the information. Furthermore, it is possible to determine whether the periodicity is high or low by changing the coefficient of the mother wavelet and performing a plurality of types of analysis.

[Fourth Embodiment]
FIG. 14 is a block diagram of the image analysis unit 92 that determines the state of an image used in this embodiment. Other configurations are the same as those in the first to third embodiments. In this embodiment, an electrophotographic printer is also used. In FIG. 14, the two-dimensional luminance data read by the CIS 50 is temporarily stored in the transport direction storage unit 130 and the longitudinal direction storage unit 131 corresponding to the analysis range therein. FIG. 15 shows an image area being read in this embodiment. The transport direction storage unit 130 and the longitudinal direction storage unit 131 store three analysis ranges each having a different position. Therefore, the processing after the density conversion unit 111 is calculated a total of six times. The analysis range stored in the transport direction storage unit 130 is 5 mm in the longitudinal direction of the CIS 50 and 420 mm in the transport direction of the medium. The analysis range stored in the longitudinal direction storage unit 131 is 300 mm in the longitudinal direction of the CIS. The size is 5 mm in the conveyance direction of the medium. Three different locations are stored. The positions of the analysis range are, for example, near the center and near both ends in each direction as shown in FIG.

  The data converted from luminance to density in the density conversion unit 111 is reduced to 1/16 by the reduction unit 112, and the one-dimensional conversion unit 113 averages the density values for the arrangement of pixels in the short side direction and performs primary processing. The normalized information (image information table) is stored. That is, for each analysis range, three image information tables are generated for each direction. Thereafter, wavelet transformation is performed on each image information table by the wavelet transformation unit 101 and the result is stored. Further, the VTF conversion unit 102 takes the product of the wavelet conversion result and the VTF for each period, and stores the value in consideration of the visual effect. The statistical processing unit 103 stores the maximum value Wmax, the position bmax and the period amax of the maximum value Wmax from the analysis result for each analysis range, further obtains the peak value for each position, and calculates the peak value from the large value. A certain number of average values Wz and several average cycles az used for calculating the average value Wz are obtained in order and stored in the storage unit. The above analysis procedure is performed in the same manner as in the first embodiment for each analysis range.

  As shown in FIG. 15, in the present embodiment, analysis is performed on three regions in the transport direction and three regions in the longitudinal direction. And the maximum value about each analysis range is employ | adopted for the maximum value Wmax and the average value Wz. Since factors such as unevenness are different between the transport direction and the longitudinal direction, for convenience, the transport direction is indicated by a suffix H, and the longitudinal direction is indicated by a suffix N. Therefore, as a result of analysis, the maximum value WmaxH, its position bmaxH, its period amaxH, its average value WzH, and its average period azH are obtained for the transport direction, and its maximum value WmaxN and its position bmaxN for the longitudinal direction. The period amaxN, the average value WzN, and the average period azN are obtained. Three of these are obtained for each direction.

  FIGS. 16A and 16B show the correspondence between the frequency of inherent pitch unevenness generated by the image forming apparatus and the cause thereof. FIG. 16A shows the correspondence between the frequency and the cause in the conveyance direction. From the one with a short period (1601) such as a polygon mirror surface tilt, the development drive gear 1, development drive gear 2, development drive gear 3, photoconductor drive gear 1, photoconductor drive gear 2, photoconductor drive gear 3, development There are those having a large cycle in order, such as a sleeve pitch and a developing roller pitch (1602).

  FIG. 16B shows the cause in the longitudinal direction. The actual pitch unevenness has few periodicity, and is the element pitch of the LED used in the pre-exposure or the arrangement pitch of the stirring screw used in the developing device. These correspond to the order from the smallest cycle. These pitches are unique to the image forming apparatus, and the pitches are stored in advance in the image analysis unit 92 and the like, compared with the average period azH in the transport direction and the average period azN in the longitudinal direction. It is possible to determine that the location causing the unevenness is an abnormal location. In the actual determination, if each factor pitch unique to the image forming apparatus has a margin of about ± 2% and is within the range, the factor is determined to be the cause.

  If the cause of pitch unevenness cannot be determined by the above method, the determinations shown in Tables 1 and 2 are made. Table 1 is for the transport direction, and Table 2 is for the longitudinal direction. According to these tables, it is possible to estimate three abnormal places by estimating the abnormal places according to the values of the average period azH in the transport direction and the average period azN in the longitudinal direction. In addition to determining an abnormal location, it is also possible to determine an action for it.

In the table, when “Warning and Next” is described, there is no subsequent action. In that case, the setting is changed so as to reduce the number of screen lines of the image forming apparatus. This setting change can be performed by an operator who has received a warning, but can also be switched by the image forming apparatus. Since the number of screen lines is lower in resolution as the number of lines decreases, the gradation stability is excellent. Therefore, in the present embodiment, four types from the default 200 lines to 141 lines, 106 lines, and 85 lines are prepared and displayed. In the case of “warning and next”, the number of lines is one step lower than the current number of lines, and then the output and analysis are prompted again. For example, a threshold matrix having a size corresponding to each size is prepared, and the matrix is switched to a larger size each time the number of lines is reduced.
FIG. 17 is a flowchart of a routine for performing image analysis and feedback control in the present embodiment. First, a test print is executed by the image forming apparatus (q1). As shown in FIGS. 14 and 15, wavelet transform, VTF transform, and statistical processing are performed for the transport direction and the longitudinal direction, and analysis results for the respective directions are obtained (q2). Analysis can be performed in the same manner as in the first embodiment.

  Among them, paying attention to the average period azH in the conveyance direction and the average period azN in the longitudinal direction, the average period azH in the conveyance direction is compared with each pitch shown in FIG. 16A, and the average period azN in the longitudinal direction is shown in FIG. Compare with each pitch shown in (b). This comparison is performed for each of the three analysis regions in each direction. Accordingly, it is determined whether the pitch is unique to the image forming apparatus (q3). The determination is made based on whether there is an average period in the range of about ± 2% of the factor pitch shown in each FIG. An average for the three analysis regions can also be adopted. As a result of the determination, if the average period is within a predetermined range including a pre-stored pitch, the corresponding pitch and the corresponding factor are displayed on the display unit (q4), and the end or retry is urged (q5). . Note that the pitch for each factor shown in FIG. 16 is digitized and stored in advance in a ROM, a nonvolatile RAM, or the like.

  If it cannot be determined in step q8, the abnormal part is estimated as shown in Tables 1 and 2, and subsequent actions are determined (q6). In these tables, specific numerical ranges for “long”, “intermediate”, and “short” of the cycle are specified and stored in a ROM, a nonvolatile RAM, or the like. These values are determined empirically. For example, the cycle corresponding to about 500 pixels or less is “short”, the cycle corresponding to about 4800 pixels or more is “long”, and the middle is “intermediate”.

  If there is a corresponding action as a result of searching Table 1 or Table 2 (q7), an inquiry is made as to whether the action is to be executed, and a response to that is determined (q8). In Tables 1 and 2, there are two actions, “cleaning of charger” and “increasing transfer current”. If it is selected to perform an action, an action corresponding to the abnormal part is executed (q9), and termination or retry is urged (q10). For example, if the action is an increase in the transfer current, the transfer current is increased by a certain amount. If the charger is to be cleaned, it is cleaned if there is a function such as hardware that realizes this. However, in the case of an image forming apparatus in which cleaning is performed by a service person, a message for prompting cleaning of the charger is only output.

  When there is no action corresponding to the abnormal part or when it is selected not to execute the action, an inquiry is made as to whether to switch the number of lines, and a response to that is determined (q11). If it is selected to perform, the number of lines is changed to a low number (q12), and termination or retry is urged (q13).

  According to the above procedure, in this embodiment, after identifying periodic unevenness unique to the image forming apparatus, information on the location where an abnormality such as blurring or unevenness that occurs once or sporadically occurs is displayed to the user. In addition, it is possible to provide a higher quality output image by installing feedback control such as an action to relieve the phenomenon of occurrence of an abnormal image as well as being able to be transmitted to a service person.

  Further, by taking a sample for image analysis in two directions, ie, a conveyance direction of the image forming apparatus and a direction orthogonal thereto, and analyzing them, it is possible to evaluate characteristics such as image defects in the conveyance direction and the direction orthogonal thereto. As a result, for each direction, a statistical value that is a cause and a countermeasure material can be presented to the user.

  In addition, if there is periodicity, search for the pitch specific to the corresponding image forming apparatus, and in other cases, estimate the cause of the abnormality due to the size of the period, and set the conditions for setting the image forming apparatus as the subsequent action. It is also possible to perform feedback control such as changing.

[Modification]
The image analysis unit of this embodiment can be combined with the preprocessing unit of the second embodiment or the third embodiment.

  In addition, the present invention can be applied to a system composed of a plurality of devices (for example, a host computer, interface device, reader, printer, etc.), or a device (for example, a copier, a facsimile device, etc.) composed of a single device. You may apply to. Another object of the present invention is to supply a storage medium (or recording medium) in which a program code of software that realizes the functions of the above-described embodiments is recorded to a system or apparatus, and the computer (or CPU or CPU) of the system or apparatus. (MPU) can also be achieved by reading and executing the program code stored in the storage medium. In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiments, and the program code itself and the storage medium storing the program code constitute the present invention.

  Further, by executing the program code read by the computer, not only the functions of the above-described embodiments are realized, but also an operating system (OS) running on the computer based on the instruction of the program code. A case where part or all of the actual processing is performed and the functions of the above-described embodiments are realized by the processing is also included. Furthermore, after the program code read from the storage medium is written into a memory provided in a function expansion card inserted into the computer or a function expansion unit connected to the computer, the function is determined based on the instruction of the program code. This includes a case where the CPU or the like provided in the expansion card or the function expansion unit performs part or all of the actual processing, and the functions of the above-described embodiments are realized by the processing.

  As described above, according to the present invention, it is possible to accurately grasp the quality of an image without depending on the subjective evaluation of a user or a service person, and also correctly feedback control to the image forming apparatus. It is possible to do.

Block diagram of image unevenness detection means inside image forming apparatus used in the present invention The figure explaining the image forming apparatus used in the present invention The figure explaining the electrical configuration of the control board and the external input / output device inside the image forming apparatus Sectional drawing explaining CIS Top view explaining CIS Flow chart for test printing Flowchart of a routine for performing image analysis in the present invention The figure explaining the conversion state by the image analysis in this invention Block diagram of the preprocessing unit 100 in the second embodiment Flowchart of a routine for performing image analysis in the second embodiment The figure explaining how to obtain the average value Wz of conspicuous unevenness Block diagram of the pre-processing unit 100 in the third embodiment Flowchart of a routine for performing image analysis in the third embodiment The block diagram of the image nonuniformity detection means inside the image forming apparatus in 4th Embodiment The figure explaining the image area | region currently read in 4th Embodiment (A) The figure which shows the specific pitch nonuniformity which the image forming apparatus of the conveyance direction in 4th Embodiment produces | generates, (b) The figure which shows the peculiar pitch nonuniformity which the image forming apparatus of the longitudinal direction in 4th Embodiment produces | generates. Flowchart of a routine for performing image analysis and feedback control in the fourth embodiment The figure of the VTF conversion table calculated in the VTF conversion part in this invention

Explanation of symbols

1: Reader scanner unit 10: CCD
20: Printer unit 21: Semiconductor laser 26: Photoconductor drum 37: Pair of transport rollers (upstream side)
38: Conveying roller pair (downstream)
50: CIS
100: Pre-processing unit 101: Wavelet transform unit 102: VTF transform unit 103: Statistical processing unit

Claims (14)

An image evaluation apparatus for evaluating the quality of an image formed by a color material on a medium,
Input means for inputting an image formed on the medium;
Wavelet conversion means for performing wavelet conversion on the image information;
Visual characteristic conversion means for further applying weighting conversion according to visual frequency characteristics for the coefficient value converted by the wavelet conversion means;
Statistical processing means for statistically processing the coefficient value converted by the visual characteristic conversion means;
An image evaluation apparatus comprising: output means for outputting a statistical value processed by the statistical processing means.   The statistical processing unit calculates, as a statistical value, at least one of an average value, a maximum value, and a position and a period in the image information related to the maximum value for the coefficient value converted by the visual characteristic conversion unit. The image evaluation apparatus according to claim 1.   The statistical processing means is greater than the average value, the maximum value, the average value of the maximum value for each position, and the maximum value for each position of the coefficient value converted by the visual characteristic conversion means. The image evaluation apparatus according to claim 1, wherein at least one of an average value of a predetermined number of count values is calculated as a statistical value from the value.   Of the image information read by the input means, an average corresponding to a direction orthogonal to the transport direction is calculated by calculating an average value for each pixel row arranged in the transport direction when an image is formed on the medium. The preprocessing unit for generating a value sequence is further provided, and the wavelet transform unit performs one-dimensional wavelet transform on the average value sequence. Image evaluation device.   Among the image information read by the input means, at least corresponding to a direction orthogonal to the transport direction by calculating an average value for each pixel row arranged in the transport direction when an image is formed on the medium. Among the image information read by the input means with one average value row, the average value is calculated for each pixel row arranged in a direction orthogonal to the transport direction, and at least one corresponding to the transport direction is calculated. 4. The method according to claim 1, further comprising pre-processing means for generating an average value sequence, wherein the wavelet transform unit performs one-dimensional wavelet transform on each of the average value sequences. The image evaluation apparatus according to item.   6. The image evaluation apparatus according to claim 1, further comprising preprocessing means for performing filtering processing or reduction processing on the image information read by the input means prior to wavelet conversion.   The wavelet conversion unit performs wavelet conversion on the image information using a plurality of mother wavelets having different wave numbers, and the visual characteristic conversion unit, the statistical processing unit, and the output unit include the plurality of wave information. The image evaluation apparatus according to claim 1, wherein weighting conversion, statistical processing, and output are performed for each count value using a mother wavelet.   The image evaluation apparatus according to claim 1, wherein the input unit includes a reading unit that reads an image formed on a medium and generates image information.   The image evaluation apparatus according to claim 8, wherein the reading unit reads at least one of luminance information, density information, and color information of the image as the image information.   The image evaluation according to any one of claims 1 to 9, further comprising means for estimating an abnormal location based on a statistical value output by the output means and outputting the estimated abnormal location. apparatus. Image forming means for forming an image with a color material on a medium;
An image forming apparatus comprising: the image evaluation apparatus according to claim 1 for evaluating an image formed on a medium by the image forming unit.   The image evaluation apparatus is configured to estimate an abnormal location based on a statistical value output from the output unit, to output the estimated abnormal location, and to output the estimated abnormal location by the image forming unit. The image forming apparatus according to claim 11, further comprising means for reducing a resolution of an image to be formed. An image evaluation method for evaluating the quality of an image formed by a color material on a medium,
An input step for inputting an image formed on the medium;
A wavelet conversion step of performing wavelet conversion on the image information;
A visual characteristic conversion step of further applying a weighting conversion according to a visual frequency characteristic for the coefficient value converted by the wavelet conversion step;
A statistical processing step of statistically processing the coefficient value converted by the visual characteristic conversion step;
An image evaluation method comprising: an output step of outputting a statistical value processed by the statistical processing step. A program for evaluating the quality of an image formed of a color material on a medium by a computer,
An input step for inputting an image formed on the medium;
A wavelet conversion step of performing wavelet conversion on the image information;
A visual characteristic conversion step of further applying a weighting conversion according to a visual frequency characteristic for the coefficient value converted by the wavelet conversion step;
A statistical processing step of statistically processing the coefficient value converted by the visual characteristic conversion step;
A program for causing a computer to execute an output step of outputting a statistical value processed by the statistical processing step.