Image quality evaluation device, image forming apparatus, and image quality evaluation method

Abstract

The image quality evaluation device includes: a conversion unit that converts image data into two-dimensional arrangement data of brightness values of each pixel of the above-mentioned image; a processing unit that performs averaging processing on each pixel of the two-dimensional arrangement data based on a plurality of filter sizes; and an evaluation unit that evaluates the image quality using the processing result of the processing unit.

Description

Technical Field

[0001] The present invention relates to an image quality evaluation device, an image forming device and an image quality evaluation method. Background Art

[0002] In an image forming apparatus or the like, an output image output to a recording medium may be different from an image on image data due to density fluctuations such as density unevenness, and therefore the image quality of the output image needs to be evaluated.

[0003] As a conventional image quality evaluation method, for example, Patent Document 1 discloses a structure in which image data in each of a plurality of processing areas in an image is subjected to frequency analysis (Fourier transform), power spectrum values ​​of specific frequencies are extracted, and quality determination of density unevenness is performed.

[0004] Patent Document 2 discloses a configuration in which variation data of image characteristic values ​​are divided into fixed intervals, and the quality of an image is evaluated based on the image characteristic values ​​of each divided interval.

[0005] In addition, Patent Document 3 discloses a structure for calculating the difference between the average brightness of the center part and the average brightness of the peripheral part of the brightness data of a two-dimensional image for each area, making a histogram representing the frequency of the difference, and evaluating the brightness unevenness on the image based on the total frequency sum value obtained by adding the frequencies of the differences greater than a threshold.

[0006] Patent Document 1: Japanese Patent Application Laid-Open No. 9-68497

[0007] Patent Document 2: Japanese Patent Application Publication No. 2006-123451

[0008] Patent Document 3: Japanese Patent Application Publication No. 2007-198850

[0009] However, even if an image is evaluated as unqualified in the evaluation of the device, there is still an image that can be evaluated as qualified in the evaluation based on human vision (sensitivity). Therefore, in the structures of Patent Documents 2 and 3, the correlation with the evaluation based on human vision becomes poor, and there is a concern that appropriate image quality evaluation cannot be performed.

[0010] In Patent Document 1, although the specific frequency is a frequency that takes into account human visual characteristics (sensitivity), since the configuration is to perform frequency analysis, a huge number of calculations must be performed in the device, resulting in a problem that the image quality evaluation time is long. Summary of the invention

[0011] An object of the present invention is to provide an image quality evaluation device, an image forming device, and an image quality evaluation method that can obtain correlation with evaluation based on human sensitivity and can easily evaluate image quality.

[0012] The image quality evaluation device of the present invention comprises:

[0013] an acquisition unit that acquires image data of an image output to a recording medium;

[0014] a conversion unit, which converts the image data acquired by the acquisition unit into two-dimensional arrangement data of brightness values ​​of each pixel of the image;

[0015] a processing unit that performs averaging processing based on a plurality of filter sizes on each pixel of the two-dimensional array data; and

[0016] The evaluation unit evaluates the image quality of the image using the processing result of the processing unit.

[0017] The image forming apparatus of the present invention comprises:

[0018] An image forming unit that forms an image;

[0019] a control unit that controls the image forming unit based on a predetermined image forming condition; and

[0020] The above-mentioned image quality evaluation device.

[0021] The image quality evaluation method of the present invention is an image quality evaluation method used by an image quality evaluation device.

[0022] acquiring image data of an image output to a recording medium,

[0023] The acquired image data is converted into two-dimensional array data of brightness values ​​of each pixel of the image,

[0024] Averaging processing based on a plurality of filter sizes is performed on each pixel of the two-dimensional array data composed of each pixel of the image.

[0025] The image quality of the image is evaluated using the processing result of the averaging process.

[0026] According to the present invention, it is possible to obtain correlation with evaluation based on human sensitivity and to easily evaluate image quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a diagram showing a schematic configuration of an image forming apparatus according to an embodiment of the present invention.

[0028] Figure 2 This is a block diagram showing the main functional structure of the image forming apparatus.

[0029] Figure 3 This is a diagram showing two-dimensional array data divided into a plurality of evaluation areas.

[0030] Figure 4 This is a diagram showing an example of visual spatial frequency characteristics.

[0031] Figure 5 It is a diagram for explaining the averaging process.

[0032] Figure 6 FIG. 1 is a diagram showing an example of two types of average values ​​based on two filter sizes.

[0033] Figure 7 This is a flowchart showing an example of an operation example when the image quality evaluation control in the image quality evaluation unit is executed.

[0034] Figure 8 These are the experimental results of the image quality evaluation control in this embodiment. DETAILED DESCRIPTION

[0035] Hereinafter, embodiments of the present invention will be described in detail based on the drawings. Figure 1 This is a diagram showing a schematic configuration of an image forming apparatus 1 according to an embodiment of the present invention.

[0036] The image forming apparatus 1 is an inkjet image forming apparatus that records an image on a recording medium P. The image forming apparatus 1 includes a paper feeding unit 10 , an image forming unit 20 , a paper discharge unit 30 , and a control unit 40 .

[0037] The image forming apparatus 1 conveys the recording medium P stored in the paper feed unit 10 to the image forming unit 20 under the control of the control unit 40 , discharges ink onto the recording medium P in the image forming unit 20 to record an image, and conveys the recording medium P with the image recorded thereon to the paper discharge unit 30 .

[0038] Specifically, the image forming apparatus 1 records a color image on the recording medium P by superimposing and outputting four colors of yellow (Y), magenta (M), cyan (C), and black (K) at a predetermined recording grayscale number on the recording medium P.

[0039] As the recording medium P, in addition to paper such as plain paper and coated paper, various media such as cloth or sheet-like resin that can fix ink deposited on the surface can be used.

[0040] The paper supply unit 10 includes a paper supply tray 11 for storing recording media P, and a medium supply unit 12 for conveying and supplying the recording media P from the paper supply tray 11 to the image forming unit 20. The medium supply unit 12 includes a wheel-shaped belt supported by two rollers on the inner side, and conveys the recording media P from the paper supply tray 11 to the image forming unit 20 by rotating the rollers in a state where the recording media P is placed on the belt.

[0041] The image forming section 20 includes a conveying section 21 , a delivery unit 22 , a heating section 23 , a head unit 24 , an irradiation section 25 , a reading section 26 , a delivery section 27 , and the like.

[0042] The conveying unit 21 holds the recording medium P placed on the conveying surface of a cylindrical conveying drum 211. The conveying drum 211 is conveyed along the conveying surface of the cylindrical conveying drum 211. Figure 1 The conveyance drum 211 rotates and moves in a circular motion around a rotation axis (cylindrical axis) extending in the X direction perpendicular to the drawing, so as to convey the recording medium P on the conveyance drum 211 in the conveyance direction along the conveyance surface.

[0043] The conveyance drum 211 includes claws and an air suction unit (not shown) for holding the recording medium P on its conveyance surface. The recording medium P is held on the conveyance surface by the claws pressing the end thereof and the air suction unit sucking the recording medium P to the conveyance surface.

[0044] The handover unit 22 is disposed between the medium supply unit 12 and the conveying unit 21 of the paper supply unit 10 , and holds and picks up one end of the recording medium P conveyed from the medium supply unit 12 by the swing arm unit 221 , and hands it to the conveying unit 21 via the handover drum 222 .

[0045] The heating unit 23 is provided between the arrangement position of the delivery drum 222 and the arrangement position of the head unit 24, and heats the recording medium P conveyed by the conveying unit 21 so that the temperature of the recording medium P becomes within a predetermined temperature range. The heating unit 23 includes, for example, an infrared heater, and the infrared heater is energized based on a control signal supplied from the control unit 40 to generate heat.

[0046] The head unit 24 records an image by discharging ink onto the recording medium P from nozzle openings provided on an ink discharge surface facing the transport surface of the transport drum 211 at appropriate timing corresponding to the rotation of the transport drum 211 holding the recording medium P.

[0047] The head unit 24 is configured so that the ink discharge surface is separated from the conveying surface by a predetermined distance. In the image forming apparatus 1 of the present embodiment, four head units 24 corresponding to the four colors of ink Y, M, C, and K are arranged side by side at a predetermined interval in the order of colors Y, M, C, and K from the upstream side in the conveying direction of the recording medium P.

[0048] The head unit 24 is used at a fixed position when recording an image, and records the image in a single pass by sequentially discharging ink at predetermined intervals (transport direction intervals) at different positions in the transport direction according to the transport of the recording medium P. Alternatively, the head unit may record the image in other methods such as a scanning method.

[0049] In addition, the structure of the head unit 24 is not limited to the above structure as long as a plurality of recording elements are provided at mutually different positions in the X direction.

[0050] The irradiation unit 25 is arranged over the width of the conveying unit 21 in the X direction, and irradiates the recording medium P placed on the conveying unit 21 with electromagnetic waves (for example, ultraviolet rays with a wavelength of 395 nm) to solidify and fix the ink discharged on the recording medium P. The irradiation unit 25 is arranged to face the conveying surface between the arrangement position of the head unit 24 and the arrangement position of the delivery drum 271 of the delivery unit 27 in the conveying direction.

[0051] The reading unit 26 is provided on the downstream side of the irradiation unit 25 in the conveying direction, and reads the output image (ink) formed on the recording medium P. The information of the output image read by the reading unit 26 is the RGB value (R component, G component, B component) of each pixel, and is output to the control unit 40, the image quality evaluation unit 100 described later, and the like.

[0052] The delivery section 27 includes a belt ring 272 having a wheel-shaped belt supported by two rollers on the inner side, and a cylindrical transfer drum 271 that transfers the recording medium P from the conveying section 21 to the belt ring 272. The recording medium P transferred from the conveying section 21 to the belt ring 272 via the transfer drum 271 is transported by the belt ring 272 and delivered to the paper discharge section 30.

[0053] The paper discharge unit 30 includes a plate-shaped paper discharge tray 31 on which the recording medium P fed from the image forming unit 20 by the delivery unit 27 is placed.

[0054] Figure 2 1 is a block diagram showing the main functional structure of the image forming apparatus 1. The image forming apparatus 1 includes a control unit 40, a head unit driving unit 50, a conveying driving unit 60, an image processing unit 70, an input / output interface 80, and an image quality evaluation unit 100. The image quality evaluation unit 100 corresponds to the "image quality evaluation device" of the present invention.

[0055] The control unit 40 includes a CPU 41 (Central Processing Unit), a RAM 42 (Random Access Memory), a ROM 43 (Read Only Memory), and a storage unit 44 , and centrally controls the overall operation of the image forming apparatus 1 .

[0056] The CPU 41 reads various control programs and setting data stored in the ROM 43 and stores them in the RAM 42 , and executes the programs to perform various calculation processes.

[0057] The RAM 42 provides a working storage space for the CPU 41 and stores temporary data. The RAM 42 may also include a nonvolatile memory.

[0058] The ROM 43 stores various control programs, setting data, etc. executed by the CPU 41. Instead of the ROM 43, a rewritable nonvolatile memory such as an EEPROM (Electrically Erasable Programmable Read Only Memory) or a flash memory may be used.

[0059] The storage unit 44 stores a print job input from an external device (not shown) via the input / output interface 80 and image data of an image recorded by the print job. As the storage unit 44, for example, a HDD (Hard Disk Drive) can be used, and a DRAM (Dynamic Random Access Memory) can also be used in combination.

[0060] The head unit driving unit 50 supplies a driving signal corresponding to the image data to the recording element of the head unit 24 at an appropriate timing based on the control of the control unit 40 , thereby causing ink of an amount corresponding to the pixel value of the image data to be discharged from the nozzles of the head unit 24 .

[0061] The conveying drive unit 60 supplies a driving signal to a conveying drum motor provided on the conveying drum 211 based on a control signal supplied from the control unit 40, so as to rotate the conveying drum 211 at a predetermined speed and timing. In addition, the conveying drive unit 60 supplies a driving signal to a motor for operating the medium supply unit 12, the delivery unit 22, and the delivery unit 27 based on a control signal supplied from the control unit 40, so as to supply the recording medium P to the conveying unit 21 and discharge the recording medium P from the conveying unit 21.

[0062] The image processing unit 70 performs predetermined image processing on the image data stored in the storage unit 44, and stores the obtained image data in the storage unit 44. This image processing includes color conversion processing, grayscale correction processing, pseudo halftone processing, etc. in addition to correction processing for correcting the image data by applying a correction table (not shown) to the image data.

[0063] The input / output interface 80 is connected to an input / output interface of an external device (eg, a personal computer) to mediate data transmission and reception between the control unit 40 and the external device. The input / output interface 80 is composed of, for example, various serial interfaces, various parallel interfaces, or a combination thereof.

[0064] The image quality evaluation unit 100 includes a CPU, RAM, and ROM (not shown), and evaluates the image quality of an output image formed on a recording medium P. The output image is, for example, a solid image of a predetermined color. The image quality evaluation unit 100 includes a conversion unit 110, a segmentation unit 120, a determination unit 130, a processing unit 140, and an evaluation unit 150.

[0065] The conversion unit 110 obtains the information (image data) of the output image read by the reading unit 26, and converts the information (RGB value) of the output image into a predetermined two-dimensional arrangement data. The two-dimensional arrangement data is data in which the brightness value of each pixel is arranged in the vertical direction and the horizontal direction. In addition, in the present embodiment, the horizontal direction of the two-dimensional arrangement data corresponds to the conveying direction of the recording medium P, and the vertical direction of the two-dimensional arrangement data corresponds to the width direction of the recording medium P.

[0066] The brightness values ​​are arranged corresponding to the pixel positions of the output image. The brightness value is calculated, for example, as an 8-bit (0 to 255) value using the formula of 0.299×R component+0.587×G component+0.114×B component.

[0067] In addition, the brightness value is in the range of 0 to 255 in the case of 8 bits, but since it is a value based on a solid image of a specified color, the range of deviation of each brightness value is easily limited to a relatively narrow range. Therefore, in the following processing, the brightness value can also be normalized within the deviation range.

[0068] The dividing unit 120 divides the two-dimensional array data into a plurality of evaluation areas. The dividing unit 120 divides the two-dimensional array data into four areas corresponding to the head units 24 in the lateral direction (the conveyance direction of the recording medium P).

[0069] For example, in Figure 3 An example of dividing the two-dimensional array data D into four areas in the horizontal direction is shown in FIG. Figure 3 In FIG. 1 , the divided regions correspond to the head unit 24 of Y, the head unit 24 of M, the head unit 24 of C, and the head unit 24 of K, respectively, from the left. In addition, the brightness values ​​are adjusted for each region according to the ratio of Y, M, C, and K.

[0070] The dividing unit 120 divides the two-dimensional array data D in the longitudinal direction, for example, for each constant number of nozzles arranged in the width direction of the recording medium P in each head unit 24. The constant number is, for example, the number of nozzles that can be driven at one time by the control unit 40. In this way, the two-dimensional array data D is divided into a plurality of evaluation regions R.

[0071] The determination unit 130 determines the filter size of one side of a square filter region used for averaging processing in each pixel constituting the two-dimensional array data based on human visual characteristics.

[0072] The human visual characteristic is, for example, a function that weights frequency bands that humans easily perceive based on their visual characteristics, that is, a visual spatial frequency characteristic (VTF: Visual Transfer Function), which can be calculated using the following equation (1).

[0073] [Formula 1]

[0074]

[0075] In formula (1), u is the response characteristic, l is the distance at which people observe the image, and μ is the spatial frequency.

[0076] For example, when l is 300 mm, the horizontal axis is the spatial frequency, and the vertical axis is the response characteristic, as shown in FIG. Figure 4 As shown, the response characteristic rises sharply as the spatial frequency changes from 0 to near 1, and after reaching the peak point, the response characteristic gradually decreases as the spatial frequency increases.

[0077] The determination unit 130 extracts the spatial frequencies whose response values ​​of the visual spatial frequency characteristics are greater than or equal to a predetermined response value T (for example, 0.5). Figure 4 In the case of the response characteristics shown, two spatial frequencies corresponding to the predetermined response value T, namely, F1 (for example, 0.24 cycles / mm) and F2 (for example, 2.84 cycles / mm), are extracted.

[0078] The decision unit 130 extracts two filter sizes based on the two spatial frequencies. Specifically, the decision unit 130 determines the filter sizes as integer values ​​closest to (1 / d)×(1 / F1) and (1 / d)×(1 / F2), respectively, when the resolution of the image is d. In other words, the visual characteristics (visual spatial frequency characteristics) are determined based on the viewing distance of the image by a person and the resolution of the image.

[0079] In this way, by selecting a range of spatial frequencies that increases in response characteristics based on human visual characteristics, it is possible to extract a filter region (filter size) corresponding to a density difference that is easily recognized when a human observes an image.

[0080] For example, when the image resolution is 300 dpi (0.038 mm / pix (pixel)) and the spatial frequencies are 0.24 cycle / mm and 2.84 cycle / mm, the filter sizes are calculated to be 10 pix (0.38 mm) and 100 pix (3.8 mm).

[0081] Furthermore, the decision unit 130 may directly use the two filter sizes calculated as described above as the filter sizes used in the processing unit 140 , or may decide the two filter sizes used in the processing unit 140 from within the range of the two filter sizes.

[0082] The processing unit 140 performs averaging processing on each of the plurality of evaluation regions R based on two filter regions each composed of two filter sizes determined by the determination unit 130. The processing unit 140 performs averaging processing on each pixel of each evaluation region R.

[0083] Specifically, the processing unit 140 sets the pixel of interest located near the center of the square filter area as the average value of all pixels in the filter area. Then, the processing unit 140 shifts the filter area and sets the pixel of interest at the shifted position as the average value of all pixels in the filter area at the position. The processing unit 140 repeatedly performs this process on all pixels.

[0084] For example, Figure 5 As shown in FIG. 1 , if the filter size of the filter area X is 3pix, the nine pixels in the filter area X are 180, 183, 185, 184, 179, 182, 186, 181, and 183, so the pixel of interest G (in Figure 5 The average value is 182. This averaging process is performed for each pixel.

[0085] The processing unit 140 performs the above-mentioned averaging process based on the two filter areas based on the two filter sizes determined by the determination unit 130. Thus, for each pixel in each evaluation area R, two average values ​​(for example, Figure 6 solid and dashed lines shown).

[0086] The evaluation unit 150 evaluates the output image using the processing result of the processing unit 140. Specifically, the evaluation unit 150 calculates the difference between two average values ​​in each pixel of each evaluation region R, and based on the difference, calculates the SN ratio of the visual characteristic for each evaluation region R. For example, the SN ratio can be calculated by the following formula (2).

[0087] [Formula 2]

[0088]

[0089] The MSD in the formula (2) is the average value of the square of the difference between two average values ​​in each pixel, and can be calculated by the formula (3). The MSD corresponds to the "parameter based on the difference between the average values" of the present invention.

[0090] [Formula 3]

[0091]

[0092] In formula (3), n is a natural number representing the number of pixels in the evaluation region R. In formula (3), y is the difference between two average values ​​in the pixel. Each number added to y represents an arbitrary pixel position in the evaluation region, and y with different numbers represents different pixel positions.

[0093] The evaluation unit 150 calculates the SN ratio for each evaluation region R as described above. The evaluation unit 150 calculates the MSD (MSD after deletion) after deleting one column of pixels at both ends in the horizontal direction in the evaluation region R, and in the evaluation region R where the amount of change in the MSD after deletion relative to the MSD before deleting the above-mentioned one column of pixels (MSD before deletion) is less than a predetermined value (for example, 10%), the evaluation unit 150 determines the MSD before deletion (the value based on the SN ratio) as the evaluation value of the evaluation region R.

[0094] In the evaluation region R where the amount of change of the post-deletion MSD relative to the pre-deletion MSD is greater than the predetermined value, after deleting pixels of one column at each of the two ends in the horizontal direction of the evaluation region R, the processes in the decision unit 130, the processing unit 140, and the evaluation unit 150 are performed again. This series of processes is performed until the amount of change of the post-deletion MSD relative to the pre-deletion MSD becomes less than the predetermined value, and the evaluation unit 150 determines the pre-deletion MSD when the amount of change becomes less than the predetermined value as the evaluation value of the evaluation region.

[0095] The evaluation unit 150 evaluates the image quality of the output image based on the maximum evaluation value among the evaluation values ​​determined for each evaluation area as described above. Specifically, the evaluation unit 150 determines that the output image has good image quality when the maximum evaluation value is less than a predetermined evaluation value, and determines that the output image has poor image quality when the maximum evaluation value is greater than the predetermined evaluation value. The predetermined evaluation value is a value that serves as an index for evaluating the image quality of the output image and can be set appropriately.

[0096] In this way, by evaluating image quality using average values ​​obtained by averaging in a filter region having a filter size based on human visual characteristics, it is possible to easily obtain a correlation between the evaluation by the device and the evaluation based on human sensitivity.

[0097] In addition, since the image quality is evaluated by comparing the average values ​​obtained by averaging two filter regions with different filter sizes, it is not necessary to perform complicated processing such as a frequency analysis such as Fourier transform. As a result, the image quality can be evaluated simply.

[0098] Furthermore, the control unit 40 changes the image forming conditions according to the evaluation result of the evaluation unit 150. Specifically, when the evaluation unit 150 determines that the output image is not of good quality, the control unit 40 changes the driving voltage of the head unit driving unit 50 from the driving voltage preset in the image forming apparatus 1.

[0099] For example, the driving voltage of the head unit driving section 50 is preset according to each density of the image. For example, the control section 40 controls the driving voltage of the head unit 24 corresponding to the evaluation area R having an evaluation value greater than a predetermined evaluation value to a driving voltage such that the average density is closest to the density that serves as a reference when forming an image and the density difference within the same head unit 24 and between other head units 24 is minimized.

[0100] In this way, by feeding back the evaluation result of the evaluation unit 150 to the control unit 40 , it is possible to form an image with good image quality for the print job after the output image is evaluated.

[0101] Next, an operation example when the image quality evaluation control in the image quality evaluation section 100 is executed will be described. Figure 7 This is a flowchart showing an example of an operation example when the image quality evaluation unit 100 performs image quality evaluation control. When the image forming apparatus 1 receives an image quality evaluation task, the image forming apparatus 1 appropriately performs the following operations: Figure 7 in the processing.

[0102] like Figure 7 As shown, the image quality evaluation unit 100 acquires information of an output image and converts it into two-dimensional array data (step S101). The image quality evaluation unit 100 divides the converted two-dimensional array data into a plurality of evaluation regions R (step S102).

[0103] The image quality evaluation unit 100 determines two filter sizes in the evaluation area R (step S103). The image quality evaluation unit 100 uses two filter areas based on the two filter sizes to perform averaging processing on each pixel in the evaluation area R (step S104). Then, the image quality evaluation unit 100 calculates the SN ratio of the visual characteristic using the two average values ​​for each pixel (step S105).

[0104] Next, the image quality evaluation unit 100 determines whether the amount of change in the MSD after deletion relative to the MSD before deletion is less than a predetermined value (step S106). If the result of the determination is that the amount of change is greater than the predetermined value (step S106, No), the image quality evaluation unit 100 deletes one column of pixels at each of the two ends in the horizontal direction of the evaluation area R (step S107). Thereafter, the process returns to step S103.

[0105] On the other hand, when the amount of change is less than or equal to the predetermined value (step S106 , Yes), the image quality evaluation section 100 determines the evaluation value of the evaluation region R (step S108 ).

[0106] Next, the image quality evaluation unit 100 determines whether the evaluation values ​​of all the evaluation regions R have been determined (step S109 ). If the result of the determination is that the evaluation values ​​of all the evaluation regions R have not been determined (step S109 , No), the process returns to step S103 .

[0107] On the other hand, when the evaluation values ​​of all the evaluation regions R are determined (step S109 , Yes), the image quality evaluation unit 100 determines whether the maximum value of the evaluation values ​​is equal to or greater than a predetermined evaluation value (step S110 ).

[0108] If the maximum value of the evaluation value is greater than the prescribed evaluation value (step S110, yes), the image quality evaluation unit 100 determines that the image quality of the output image is not good (step S111). On the other hand, if the maximum value of the evaluation value is less than the prescribed evaluation value (step S110, no), the image quality evaluation unit 100 determines that the image quality of the output image is good (step S112). After step S111 or step S112, this control ends.

[0109] According to the present embodiment constructed as described above, averaging is performed in a plurality of filter areas based on a plurality of filter sizes. In addition, in the output image, minute density changes that cannot be recognized by humans are caused due to the image formation process, the influence of the recording medium, and the influence of the reading unit 26. In the evaluation of the device, the evaluation is made taking density changes into consideration, so there is a possibility that the correlation with the evaluation based on human sensitivity becomes poor.

[0110] In contrast, in this embodiment, the evaluation value is determined using the average values ​​of multiple types obtained by averaging in multiple filter areas, so the image quality evaluation can be performed without the above-mentioned slight concentration changes. As a result, the correlation between the evaluation of the device and the evaluation based on human sensitivity can be easily obtained.

[0111] Furthermore, since the image quality is evaluated using an average value obtained by averaging in a filter region having a filter size determined based on human visual characteristics, the correlation between the evaluation by the device and the evaluation based on human sensitivity can be easily obtained.

[0112] In addition, since the image quality is evaluated by comparing the values ​​obtained by averaging two filter regions with different filter sizes, it is not necessary to perform complicated processing such as a frequency analysis such as Fourier transform. As a result, the image quality can be evaluated simply.

[0113] That is, in the present embodiment, correlation with evaluation based on human sensitivity can be obtained, and image quality evaluation can be performed simply.

[0114] Furthermore, since the SN ratio of the visual characteristic is calculated using the average value of each pixel in each evaluation region R, it is possible to quantitatively evaluate the image quality.

[0115] In addition, the viewing distance of a person is used as a function for weighting the frequency band that is easily perceived by a person in terms of visual characteristics, that is, a parameter in the spatial frequency characteristics of vision. As a result, the filter size is determined based on the viewing distance of a person, so that the spatial frequency components that are highly sensitive in the visual characteristics of a person can be easily extracted.

[0116] In addition, when the change amount of the MSD after deletion relative to the MSD before deletion is greater than a predetermined value, the pixels at both ends of the directional component of one direction of the two-dimensional arrangement in the evaluation area are removed, and the averaging process is repeated. Here, the pixels at both ends are likely to contain noise components, so by removing the pixels at both ends, a highly robust evaluation value can be calculated.

[0117] Furthermore, by feeding back the evaluation result of the evaluation unit 150 to the control unit 40 , it is possible to perform image formation of the print job with good image quality after the output image has been evaluated.

[0118] Furthermore, in the above embodiment, the averaging process is performed using two filter regions based on two filter sizes, but the present invention is not limited thereto, and the averaging process may be performed using three or more filter regions based on three or more filter sizes.

[0119] In addition, although the SN ratio of the eye-catching characteristic is used as the evaluation value in the above-mentioned embodiment, the present invention is not limited to this, and contents other than the SN ratio of the eye-catching characteristic may be used as the evaluation value.

[0120] In addition, although in the above-mentioned embodiment, when the amount of change of the MSD after deletion relative to the MSD before deletion is greater than a predetermined value, the MSD before deletion is not used as the evaluation value, and the SN ratio is recalculated based on the data after the pixels at both ends of the horizontal direction (predetermined direction) of the two-dimensional array data are deleted, the present invention is not limited to this. For example, the MSD before deletion may be used as the evaluation value when the amount of change of the MSD after deletion relative to the MSD before deletion is greater than a predetermined value.

[0121] In addition, although MSD is exemplified as a parameter based on the difference of the average value in the above-mentioned embodiment, the present invention is not limited to this, and a parameter other than MSD may be used as a parameter based on the difference of the average value.

[0122] In addition, in the above-described embodiment, the filter size is determined by the determination unit 130 , but the present invention is not limited thereto, and the filter size may be acquired.

[0123] In addition, in the above-mentioned embodiment, the two-dimensional array data is divided into a plurality of evaluation areas, but the present invention is not limited thereto, and the two-dimensional array data may not be divided into a plurality of evaluation areas.

[0124] In addition, although the above-mentioned embodiment includes a conversion unit, the present invention is not limited to this, and may be configured to acquire two-dimensional array data.

[0125] In the above embodiment, the image quality evaluation unit 100 (image quality evaluation device) is included in the image forming apparatus 1 , but the present invention is not limited thereto, and for example, the image quality evaluation device may be provided separately from the image forming apparatus.

[0126] In addition, although in the above embodiment, the image quality evaluation unit 100 includes the conversion unit 110, the segmentation unit 120, the determination unit 130, the processing unit 140, and the evaluation unit 150, the present invention is not limited thereto. For example, the conversion unit, the segmentation unit, the determination unit, the processing unit, and the evaluation unit may be independently provided.

[0127] In addition, in the above-described embodiment, the reading unit 26 is provided in the image forming apparatus 1 , but the present invention is not limited thereto, and the reading unit 26 may be provided outside the image forming apparatus 1 .

[0128] In addition, although the inkjet image forming apparatus 1 is exemplified in the above-mentioned embodiment, the present invention is not limited to this, and an image forming apparatus other than the inkjet image forming apparatus may be used.

[0129] In addition, the above embodiments are only examples of embodiments when implementing the present invention, and the technical scope of the present invention is not limited by these embodiments. That is, the present invention can be implemented in various ways without departing from its purpose or its main features. For example, the shape, size, number and material of each part described in the above embodiments are only examples and can be appropriately changed for implementation.

[0130] Next, the experimental results of the image quality evaluation control in this embodiment are described. In the following experiment, the image quality evaluation control in this embodiment is performed on an output image that is a solid image of a specified color, and multiple people visually evaluate each evaluation area of ​​the output image to obtain their correlation.

[0131] Figure 8 These are the experimental results of the image quality evaluation control in this embodiment. Figure 8The vertical axis in is the evaluation value of the image quality evaluation control. The higher the value is, the higher the evaluation value is. In other words, the image quality is not good. Figure 8 The horizontal axis in is the average of the visual evaluation scores. The further to the right, the higher the evaluation score. In other words, the worse the image quality. Figure 8 The multiple drawings in represent multiple evaluation regions R.

[0132] Furthermore, in the evaluation score, among the persons who performed the visual evaluation, within a predetermined score range, the better the image quality, the lower the score is assigned.

[0133] If you observe Figure 8 , the visual evaluation score of the evaluation area R that becomes a relatively high evaluation value in the image quality evaluation control also becomes a relatively high score, and the visual evaluation score of the evaluation area R that becomes a relatively low evaluation value in the image quality evaluation control also becomes a relatively low score.

[0134] That is, it was confirmed that the image quality evaluation unit 100 in this embodiment can obtain the correlation between the evaluation result and the evaluation result of human sensitivity.

[0135] Explanation of the reference numerals: 1…image forming device, 10…paper supply unit, 11…paper supply tray, 12…medium supply unit, 20…image forming unit, 21…conveying unit, 22…handover unit, 23…heating unit, 24…head unit, 25…irradiation unit, 26…reading unit, 27…delivery unit, 30…paper discharge unit, 31…paper discharge tray, 40…control unit, 44…storage unit, 50…head unit drive unit, 60…conveying drive unit, 70…image processing unit, 80…input / output interface, 100…image quality evaluation unit, 110…conversion unit, 120…segmentation unit, 130…determination unit, 140…processing unit, 150…evaluation unit.

Claims

1. A picture quality evaluation device, in, have: an acquisition unit that acquires image data of an image output to a recording medium; a conversion unit, which converts the image data acquired by the acquisition unit into two-dimensional arrangement data of brightness values ​​of each pixel of the image; a processing unit that performs averaging processing based on a plurality of filter sizes on each pixel of the two-dimensional array data; as well as an evaluation unit that evaluates the image quality of the image using the processing result of the processing unit, The image quality evaluation device determines the plurality of filter sizes based on human visual characteristics.

2. The image quality evaluation device according to claim 1, in, The visual characteristics are spatial frequency characteristics of vision determined based on the observation distance of the image by the person and the resolution of the image.

3. The image quality evaluation device according to claim 2, in, The image quality evaluation device includes a determination unit configured to determine a plurality of filter sizes based on a plurality of frequencies at which response values ​​of visual spatial frequency characteristics are equal to or greater than a predetermined response value.

4. The image quality evaluation device according to any one of claims 1 to 3, in, The evaluation unit calculates an SN ratio of visual characteristics based on a difference between two average values ​​in each pixel of the two-dimensional array data, uses a value based on the SN ratio as an evaluation value, and determines whether the image quality of the image is good based on the evaluation value.

5. The image quality evaluation device according to claim 4, in, When the change in the parameter based on the difference of the above-mentioned average value is larger than the specified value, the above-mentioned evaluation unit does not use the value based on the above-mentioned SN ratio as the above-mentioned evaluation value based on the above-mentioned parameter, but recalculates the above-mentioned SN ratio based on the data after deleting the pixels at both ends of the specified direction of the above-mentioned two-dimensional arrangement data.

6. The image quality evaluation device according to any one of claims 1 to 3, in, The image quality evaluation device includes a dividing unit that divides the two-dimensional array data into a plurality of evaluation areas. The processing unit performs the averaging process for each of the evaluation areas based on each of the plurality of filter sizes determined for each of the evaluation areas, The evaluation unit evaluates the image quality of the image based on the processing results of the processing unit.

7. An image forming device, in, have: An image forming unit that forms an image; a control unit that controls the image forming unit based on a predetermined image forming condition; and An image quality evaluation device as claimed in any one of claims 1 to 6.

8. The image forming apparatus according to claim 7, in, The control section changes the image forming condition based on the evaluation result of the evaluation section.

9. The image forming apparatus according to claim 8, in, The image forming section includes a head unit that forms the image by discharging ink onto a recording medium. The control unit changes the driving voltage of the head unit from the image forming condition when the evaluation unit determines that the image quality of the image is not good.

10. A method for evaluating image quality, which is a method for evaluating image quality used by an image quality evaluation device. in, include: a step of acquiring image data of an image output to a recording medium; The step of converting the acquired image data into two-dimensional arrangement data of brightness values ​​of each pixel of the image; A step of performing averaging processing based on a plurality of filter sizes on each pixel of the two-dimensional array data composed of each pixel of the image; as well as The step of evaluating the image quality of the image using the processing result of the averaging processing, In the above-mentioned image quality evaluation method, the above-mentioned plurality of filter sizes are determined based on human visual characteristics.

11. The image quality evaluation method according to claim 10, in, The visual characteristics are spatial frequency characteristics of vision determined based on the observation distance of the image by the person and the resolution of the image.

12. The image quality evaluation method according to claim 11, in, The method comprises the step of determining a plurality of filter sizes at a plurality of frequencies where the response value of the visual spatial frequency characteristic is greater than or equal to a predetermined response value.

13. The image quality evaluation method according to any one of claims 10 to 12, in, The steps for evaluating the image quality of the above-mentioned image include the following steps: calculating the SN ratio of the visual characteristic based on the difference between the two average values ​​in each pixel of the above-mentioned two-dimensional arrangement data, using the value based on the SN ratio as the evaluation value, and judging whether the image quality of the above-mentioned image is good based on the above-mentioned evaluation value.

14. The image quality evaluation method according to claim 13, in, The steps for evaluating the image quality of the above-mentioned image include the following steps: when the change in the parameter based on the difference of the above-mentioned average value is greater than the specified value, based on the above-mentioned parameter, the value based on the above-mentioned SN ratio is not used as the above-mentioned evaluation value, but the above-mentioned SN ratio is recalculated based on the data after deleting the pixels at both ends of the specified direction of the above-mentioned two-dimensional arrangement data.

15. The image quality evaluation method according to any one of claims 10 to 12, in, The method further includes dividing the two-dimensional array data into a plurality of evaluation areas. The step of performing the averaging process respectively includes the steps of: performing the averaging process on each of the evaluation areas based on each of the plurality of filter sizes determined for each of the evaluation areas; The step of evaluating the image quality of the image includes the step of evaluating the image quality of the image based on the respective processing results of the step of performing the averaging processing.

16. The image quality evaluation method according to any one of claims 10 to 12, in, The image quality evaluation device is included in an image forming device, and the image forming device includes an image forming unit controlled based on predetermined image forming conditions.

17. The image quality evaluation method according to claim 16, in, The method further includes the step of changing the image forming conditions according to an evaluation result of the step of evaluating the image quality.

18. The image quality evaluation method according to claim 17, in, The image forming section includes a head unit that forms the image by discharging ink onto a recording medium. The step of changing the image forming conditions includes the step of changing the driving voltage of the head unit from the image forming conditions when it is determined in the step of evaluating the image quality that the image quality is not good.

Images