JP2021068159A - Image processing apparatus, image processing method, and program - Google Patents

Abstract

To provide an evaluation value that matches the appearance even when a break is present in a straight line.SOLUTION: An image processing apparatus of the present invention comprises: an image input unit (201) that acquires (receives input of) image data obtained by reading, with a reader (107), a line image recorded by an image forming apparatus (106) based on recording data; a detection unit (202) that detects a printing area and a non-printing area in the line image based on the image data; and an evaluation value calculation unit (203) that derives (calculates) an evaluation value for evaluating the reproducibility of the line image recorded based on the recording data by using a result of execution of predetermined processing on the image data corresponding to the non-printing area.SELECTED DRAWING: Figure 4

Description

The present invention relates to a technique for evaluating an image formed by an image forming apparatus.

Conventionally, in electrophotographic and inkjet image forming apparatus, in order to perform printing with higher image quality, the resolution of printing is increasing. In recent years, an image forming apparatus corresponding to a high resolution of 2400 dpi has been put into practical use. However, on the other hand, a thin line having a width of several tens of μm as expressed by 1 dot is output in a state unintended by the user, such as a change in the line width of the thin line, a jagged edge of the thin line, and a change in density. Sometimes.

Therefore, a technique for evaluating the reproducibility of fine lines is defined in ISO / IEC24790 or disclosed in Patent Document 1. In ISO / IEC24790, "Blurriness", "Raggedness", "Line Width", and "Character Darkness" are defined as evaluation items for the reproducibility of thin lines. Further, Patent Document 1 describes that by cutting a high frequency component at the edge of a thin line, an evaluation value indicating the jaggedness of the thin line in consideration of human separated visual acuity is calculated.

Japanese Unexamined Patent Publication No. 2002-222418

Otsu: Automatic threshold selection method based on discrimination and least squares method, IEICE Transactions, Vol. J63-D, No. 4, pp. 349-356, 1980

However, when a thin line with a width of several tens of μm is output, even if the input data is an uninterrupted line, the line may be interrupted and output. Cannot be evaluated.

That is, the above-mentioned conventional technique has a problem that even if the interrupted line is evaluated, it may be calculated as a better evaluation value than the uninterrupted line, which is different from the one visually recognized by a person.

The present invention has been made in view of the above problems, and an object of the present invention is to provide an evaluation value that matches the appearance even if there is a break in the straight line.

The image processing apparatus of the present invention is based on the acquisition means for acquiring the image data obtained by reading the line image recorded by the image forming apparatus based on the recorded data by the reading device and the image data. Reproduction of the line image recorded based on the recorded data by using the detection means for detecting the printed area and the non-printed area in the line image and the result of performing a predetermined process on the image data corresponding to the non-printed area. It is characterized by providing a derivation means for deriving an evaluation value for evaluating the property.

According to the present invention, it is possible to provide an evaluation value that matches the appearance even if there is a break in the straight line.

It is a figure which shows the hardware configuration of an image processing apparatus. It is a figure which shows the functional structure of an image processing apparatus. It is a schematic diagram of a straight line image. It is a flowchart which shows the procedure of the processing executed in the image processing apparatus. It is a flowchart which shows the procedure of the process executed in the detection part. It is a figure which showed the luminance image and the binarized image. It is a figure for demonstrating the process of obtaining the left and right edge coordinates. It is a flowchart which shows the procedure of the process which is executed in the evaluation value calculation part. It is a figure for demonstrating the approximate straight line of the left and right edges in a print area, and the coordinates used for the evaluation value calculation. It is a figure for demonstrating the calculation method of the evaluation value of jaggedness. It is a flowchart which shows the procedure of the process which is executed in the evaluation value calculation part. It is a figure for demonstrating the coordinates used for the calculation of an evaluation value. It is a figure for demonstrating the calculation method of the density | concentration evaluation value. It is a flowchart which shows the procedure of the process which is executed in the evaluation value calculation part. It is a flowchart which shows the procedure of the process executed in the detection part. It is a figure for demonstrating the process executed in the detection part.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. It should be noted that the following embodiments do not limit the present invention, and not all combinations of features described in the present embodiment are essential for the means for solving the present invention. In addition, as a supplement, the same configuration will be described with the same reference numerals.

(Embodiment 1)
In this embodiment, a mode in which the image forming apparatus reads an image formed on a recording medium and evaluates the line reproducibility of the image forming apparatus will be described. That is, the image to be evaluated is an image obtained by reading a printed matter. A method of calculating an evaluation value of jaggedness for an image including a straight line (hereinafter referred to as a straight line image) and correcting the image according to the evaluation value will be described. Here, the evaluation value of the jaggedness is one of the evaluation values for evaluating the reproducibility of the thin line. The same applies to the evaluation value related to the concentration (hereinafter referred to as the concentration evaluation value) and the evaluation value indicating the degree of interruption described in the embodiments described later.

<Hardware configuration>
FIG. 1 is a diagram showing a hardware configuration of an image forming system including an image processing device according to the present embodiment. The image processing device 100 according to the present embodiment is, for example, a personal computer or the like, and is connected to the image forming device 106. Further, each function of the image processing device 100 is realized by the personal computer executing a predetermined program. The hardware configuration of the image forming system is not necessarily limited to the configuration shown in FIG. For example, the control of the image forming apparatus 106 executed by the image processing apparatus may be realized by operating as an image processing controller built in the image forming apparatus.

The image processing device 100 includes a CPU 101, a RAM 102, a storage unit 103, an interface (I / F) 104, and a bus 105, and is connected to the image forming device 106 and the reading device 107. The CPU 101 controls the operation of the entire image forming system by using the input data and the computer program stored in the RAM 102 and the storage unit 103.

The RAM 102 is used as a storage area used by the CPU 101 for performing various processes, and also temporarily stores data necessary for image processing such as various data read from the storage unit 103 and a computer program. Used as.

The storage unit 103 stores parameters, programs, and the like for setting each unit in the image forming system. The I / F 104 functions as an interface for connecting the image processing device 100 and an external device, exchanges data with the communication device using infrared communication, wireless LAN, or the like, and is an interface for connecting to the Internet. Also works as.

Each of the above-mentioned units (CPU 101, RAM 102, storage unit 103, and I / F 104) is connected to the bus 105 and transmits / receives various data via the bus 105. The image forming apparatus 106 is a printer of an electrophotographic method, an inkjet method, or the like, and forms (records) an image on a recording medium using a coloring material based on the recorded data. The scanning device 107 is, for example, an image scanner, which reads a document such as characters and photographs as digital data, and transfers the acquired data to the image processing device 100 via the I / F 104.

<Functional configuration>
Next, various functions realized by the CPU 101 executing various software (computer programs) stored in the storage unit 103 will be described. FIG. 2 is a diagram showing a functional configuration for executing image evaluation of the image processing apparatus according to the present embodiment. As shown in FIG. 2, the image processing device 100 includes an image input unit 201, a detection unit 202, an evaluation value calculation unit 203, and a setting unit 204.

The image input unit 201 acquires image data of a straight line image in response to an instruction (command) from the CPU 101. As described above, the image data acquired here is digital data obtained by the reading device 107 reading the printed matter output by the image forming device 106. The image data of this linear image is, for example, R (red), G (green), and B (blue) data, and is image data in which the pixel value of one pixel is represented by 8 bits. Hereinafter, the description of the linear image of the image data acquired by the image input unit 201 will be supplemented with reference to FIG.

FIG. 3 is a schematic view of a linear image obtained by cutting out a line region and enlarging the image read by the reading device 107. In the present embodiment, in order to evaluate the line reproducibility of the image forming apparatus 106, the image forming apparatus 106 prints on a recording medium based on the image data including the line chart shown in FIG. 3 (e). Note that FIG. 3E is a diagram schematically showing image data composed of a plurality of pixels. For example, when the chart image data consists of 2-bit pixel values, it means that dots are printed on the pixels that form the thin line, and 0 that means that the dots are not printed on the pixels in the area that does not form the thin line. Is stored. Here, when the image forming apparatus 106 prints based on the chart image data shown in FIG. 3 (e), it is assumed that a line having a width of several tens of μm (about 50 to 80 μm) is printed on the recording medium. Further, the printed recording medium is read by the reading device 107 to acquire image data of a linear image used for evaluation. At this time, the reading device 107 is made to read so that a line is formed in the vertical direction in the image. In the case of an image in which lines are formed in the horizontal direction (an image in which FIG. 3A is rotated by 90 degrees), the image is read by 90 degrees (or by 90 degrees) before being read by the reading device 107. The image may be such that lines are formed in the vertical direction by rotating the image (270 degrees). Therefore, as the straight line image, as shown in FIGS. 3A and 3B, an image including a line oriented in the vertical direction in the image data is targeted. When the image forming apparatus 106 prints based on FIG. 3 (e), ideally, a straight line without rattling or interruption as shown in FIG. 3 (e) is formed on the recording medium. desirable. However, in reality, the outline of the line is jagged and jagged as shown in FIG. 3A, or the line is interrupted as shown in FIG. 3B. In this embodiment, since one line is evaluated, when two straight lines exist on the image data as shown in FIG. 3C, one straight line is used as shown in FIG. 3A. It is necessary to separate (correct) each one. Further, it is also necessary to correct the image data in the same manner for an image in which the direction of the straight line as shown in FIG. 3D is not the vertical direction and the printing material is scattered. This correction will be described in the fourth embodiment described later. The degree of deterioration in line reproducibility by the image forming apparatus 106, such as the jaggedness and breaks in the lines shown in FIGS. 3A to 3D as described above, is appropriately evaluated.

Returning to FIG. 2, the detection unit 202 detects a print area and a non-print area, respectively, with respect to the linear image input by the image input unit 201 in response to an instruction from the CPU 101. Here, the print area is an area in which a recording material such as toner or ink is printed on the recording medium, and the non-print area is an area in which the recording material is printed on the recording medium as a part of a line. This is the area where the recording material was not printed even though it was the area to be printed. That is, the non-printing area is an area shown as a break portion of the linear image.

The evaluation value calculation unit 203 calculates the evaluation value of the linear image based on the print area and the non-print area detected by the detection unit 202 in response to the instruction from the CPU 101. In the present embodiment, the evaluation value of the jaggedness is calculated as the evaluation value. The calculation method will be described later with reference to FIG.

The setting unit 204 controls the setting of the image forming apparatus 106 based on the evaluation value calculated by the evaluation value calculation unit 203 in response to the instruction from the CPU 101. The corrected result is transferred to the image forming apparatus 106, and the image forming apparatus 106 forms an image on the recording medium by reflecting the corrected result.

Although the functions of the image processing apparatus according to the present embodiment have been described above, it is not necessary for the CPU 101 to realize all of these functions by executing a computer, and a dedicated processing circuit corresponding to each functional block is provided. You may do so.

<Processing procedure in the image processing device>
Next, the procedure of the processing executed by the image processing apparatus 100 will be described based on the functional configuration of the image processing apparatus 100 described with reference to FIG. FIG. 4 is a flowchart showing a processing procedure executed by the image processing apparatus 100. The symbol "S" in the description of the flowchart represents a step. The same applies to the description of the following flowchart.

In S401, the image input unit 201 acquires image data of a straight line image obtained by reading a recording medium on which a line chart image is printed. Here, the image data of the straight line image is the image data in which each of RGB is represented by 8 bits as described above. In S402, the detection unit 202 detects a printed area and a non-printed area in the linear image acquired in S401, respectively. The details of the processing of S402 will be described later with reference to FIG.

In S403, the evaluation value calculation unit 203 calculates an evaluation value indicating the jaggedness based on the printed area and the non-printed area detected in S402. The details of the processing of S403 will be described later with reference to FIG.

In S404, the setting unit 204 determines whether or not the evaluation value calculated in S403 satisfies a predetermined condition. Here, the setting unit 204 determines whether or not the evaluation value of the jaggedness calculated in S403 is equal to or greater than the threshold value. This threshold value may be arbitrarily set by the user. For example, the evaluation result can be prepared as a data group in advance and set based on this data group. Here, the evaluation value of the jaggedness shall indicate that the larger the value, the greater the jaggedness.

Therefore, in the present embodiment, the setting unit 204 determines that it is necessary to improve the line reproducibility of the image forming apparatus 106 if the evaluation value of the jaggedness is equal to or higher than the set threshold value, and shifts the process to S405. Let me. Further, the setting unit 204 determines that the image correction is not necessary if the evaluation value of the jaggedness is less than the set threshold value, and ends the process shown in FIG.

In S405, when the setting unit 204 determines in S404 that it is necessary to improve the line reproducibility of the image forming apparatus 106, the setting unit 204 changes the setting of the image forming apparatus 106. Here, some examples are given as processes for changing the settings of the image forming apparatus 106.

For example, the line reproducibility can be improved by changing the setting of the print screen shape stored in the image forming apparatus 106. Such a change in setting is effective when the screen used in the screen processing for printing by the image forming apparatus 106 interferes with the linear image data and a break occurs. Here, as the screen to be changed, for example, a high-line number line screen having a screen angle such that the difference between the direction of the straight line and the screen angle becomes large is desirable.

Further, the line reproducibility can be improved by increasing the print density setting of the image forming apparatus 106 or increasing the laser output if the image forming apparatus 106 is an electrophotographic printer. In these processes, more recording material adheres to the recording medium, so that the breakage of the straight line can be suppressed. Therefore, it is effective when the jaggedness is deteriorated due to the interruption of the straight line.

Further, if the image data for printing itself input to the image forming apparatus 106 can be modified, a line in the image data is detected, and dots are forcibly added in the line width direction of the detected line to obtain the image data. The line reproducibility can also be improved by increasing the line width above. If the line width of the line in the input image data is wide, the image forming apparatus 106 can reproduce the line more stably, and the breakage of the straight line can be suppressed. Therefore, it is effective when the jaggedness is deteriorated due to the interruption of the straight line.

As described above, based on the evaluation value (more specifically, based on the evaluation value being equal to or higher than a predetermined threshold value), the line width of the straight line image is thickened with respect to the image data for printing. Corrections can be made. Whether or not the original data can be modified may be determined by whether or not permission is granted according to user settings and the like. Further, when the setting unit 204 completes the correction of the straight line in S405, the setting unit 204 ends the process shown in FIG.

<Processing in the detector>
Next, the process of S402 executed by the detection unit 202 will be described with reference to FIG. FIG. 5 is a flowchart showing the procedure of the process executed by the detection unit 202, and shows the process of S402 described in detail.

In S501, the detection unit 202 extracts the luminance component of the linear image (hereinafter, the image from which the luminance component is extracted is referred to as a luminance image). To extract the luminance component, the RGB value of the linear image may be converted into the CIEXYZ color space and the Y value of the XYZ values may be used as the luminance component, or the G value of the RGB image may be used as the luminance component.

Hereinafter, a method of converting the RGB value of the linear image into the XYZ value of the CIEXYZ color space will be described. Regarding the RGB values of the straight line image, the RGB values of the xth pixel in the horizontal direction and the yth pixel in the vertical direction from the upper left of the straight line image are R (x, y), G (x, y), and B (x, respectively. , Y).

First, as shown in the following equation (1), the gamma characteristic of the reader 107 that acquired the image data after normalizing the 8-bit R (x, y) data to a value of 0 or more and 1 or less. Multiply by γ to obtain the luminance linear data R'(x, y). Similarly, as shown in the following equations (2) and (3), the luminance linear data G'(x, y), B'(from the 8-bit G (x, y), B (x, y) data Find x, y).

Next, the color data represented by R'G'B'is converted into the tristimulus values X, Y, Z of the CIEXYZ color system. The transformation matrix for converting the brightness linear data R'G'B'to the tristimulus value XYZ is, for example, a matrix of 3 rows and 3 columns, and 3 corresponding to this conversion matrix and the brightness linear data R'G'B' The matrix product with the row-and-column matrix is shown as a 3-by-1 matrix corresponding to the tristimulus value XYZ values. By calculating the matrix product in this way, the luminance linear data R'G'B'can be converted into the tristimulus value XYZ. Specifically, it is converted into X, Y, and Z by the conversion formulas shown in the following formulas (4) to (6). In the following equations (4) to (6), m11 to m33 are elements of the transformation matrix M.

In S502, the detection unit 202 executes a binarization process on the luminance image converted in S501 in order to separate the luminance image into a print area and a non-print area. Here, the binarization process is a process of assigning "1" when the pixel value of the luminance image is equal to or more than the threshold value and "0" when the pixel value is less than the threshold value.

The threshold value may be determined by using, for example, the method disclosed in Non-Patent Document 1. Further, this threshold value may be obtained from the ratio of the numerical range that the pixel value of the luminance image can take.

As a supplement, FIG. 6 is used to illustrate a luminance image and an image after binarization processing (hereinafter, referred to as a binarized image). 6 (a) schematically shows a luminance image before the binarization process, and FIG. 6 (b) schematically shows an image after the binarization process. It should be noted that one square shown in FIG. 6 corresponds to one pixel, and the shade of the filled square corresponds to the size of the pixel value.

Since the luminance image of FIG. 6 (a) has multiple gradations, the filled squares have shading, but the binarized image of FIG. 6 (b) is printed because it has two gradations. It is indicated by black (“0”), which is an area, and white (“1”), which is an unprinted area.

Returning to FIG. 5, in the processes from S503 to S509, the detection unit 202 executes a loop process on the binarized image. Here, it is assumed that the binarized image is a two-dimensional array and is represented by an M × N matrix in which the number of rows of the binarized image is M and the number of columns is N. In this case, for example, in the binarized image shown in FIG. 6B, since it is a binarized image of 17 rows and 15 columns, M = 17 and N = 15 are set.

In S503, the detection unit 202 determines whether or not the variable i indicating the scanning order in the column direction of the binarized image is M or less, which is the number of rows of the binarized image. The initial value of the variable i is set to 1. In this case, for example, in the binarized image shown in FIG. 6B, the detection unit 202 shifts the process to S504 if the variable i is 17 or less, and loops if the variable i is larger than 17. Is terminated, and the processing of S402 is terminated.

In S504, the detection unit 202 obtains the coordinate value of the left edge of the straight line in the i-th row of the binarized image. Specifically, in the i-th row of the binarized image, scanning is performed from the first column to the right, and the (x, y) coordinates at which the pixel value of the binarized image changes from "1" to "0" are set to two. It is stored in the dimensional arrays L (i, 1) and L (i, 2). This two-dimensional array L shows the coordinate values of the left edge of the straight line. If all the columns from the first column to the Nth column are "1", "-1" is stored in L (i, 1), and if the first column is "0", "1" is stored. Store in L (i, 1).

Here, the description of the process of S504 will be supplemented with reference to FIG. 7. FIG. 7A is a schematic diagram of the processing of S504 and a diagram showing two-dimensional arrays L, Lp, and Lnp. The image shown in FIG. 7 (a) is the same as the binarized image of FIG. 6 (b), and in FIG. 7 (a), when the variable i = 1, the pixel values are “1” to “0”. The coordinates when changing to are (x, y) = (6,1). Therefore, "6" is stored in L (1,1) and "1" is stored in L (1,2).

In S505, the detection unit 202 obtains the coordinate value of the right edge of the straight line in the i-th row of the binarized image. Specifically, similarly to the processing of S504, in the i-th row of the binarized image, scanning is performed from the Nth column to the left, and the pixel value of the binarized image changes from "1" to "0" ( The x, y) coordinates are stored in the two-dimensional arrays r (i, 1) and r (i, 2). This two-dimensional array r shows the coordinates of the right edge of the straight line. If all the columns from the Nth column to the 1st column are "1", "-1" is stored in r (i, 1), and if the Nth column is "0", "1" is stored. Store in r (i, 1).

Here, the description of the process of S505 will be supplemented with reference to FIG. 7. FIG. 7B is a schematic diagram of the processing of S505 and a diagram showing two-dimensional arrays r, rp, and rnp. The image shown in FIG. 7 (b) is the same as the binarized image of FIG. 6 (b), and in FIG. 7 (b), when the variable i = 1, the pixel values are "1" to "0". The coordinates when changing to are (x, y) = (9,1). Therefore, "9" is stored in r (1,1) and "1" is stored in r (1,2).

Returning to FIG. 5, in S506, the detection unit 202 determines whether the i-th line of the binarized image is a print area or a non-print area. Specifically, the detection unit 202 determines whether L (i, 1) ≠ -1 and r (i, 1) ≠ -1.

When L (i, 1) ≠ -1 and r (i, 1) ≠ -1, the detection unit 202 shifts the process to S507 and sets the i-th line as the print area. The detection unit 202 uses two-dimensional arrays storing the left and right edge coordinates (that is, the position coordinates of both ends in the width direction of the straight line) of the print area of the straight line image as Lp (i) and rp (i), respectively. (I) is stored in Lp (i), and r (i) is stored in rp (i). As a supplement, FIG. 7 (a) shows a two-dimensional array Lp, and FIG. 7 (b) shows a two-dimensional array rp.

On the other hand, when L (i, 1) ≠ -1 and r (i, 1) ≠ -1, the detection unit 202 shifts the processing to S508 and sets the i-th line as the non-printing area. To do. The detection unit 202 uses two-dimensional arrays storing the left and right edge coordinates of the non-printed area of the linear image as Lnp (i) and rnp (i), respectively, and L (i) as Lnp (i) and r (i). Is stored in rnp (i). As a supplement, FIG. 7 (a) shows a two-dimensional array Lmp, and FIG. 7 (b) shows a two-dimensional array rnp.

In S509, the detection unit 202 increments the variable i by 1 and returns the process to S503. By executing the processing as described above (that is, by executing the processing as shown in FIGS. 7A and 7B), the 4, 5, 14 and 15th lines of the binarized image are not printed. It becomes an area, and the (x, y) coordinates of the line corresponding to the non-printed area are stored in the two-dimensional arrays Lnp and rnp. Further, the other lines are printed areas, and the (x, y) coordinates of the lines corresponding to the print areas are stored in the two-dimensional arrays Lp and rp. Then, when the processing of S402 (that is, the detection processing of the printed area and the non-printed area of the linear image) is completed, the image processing apparatus 100 shifts the processing to S403.

<Processing in the evaluation value calculation unit>
Next, with respect to the process of S403 executed by the evaluation value calculation unit 203 (that is, the process of calculating the evaluation value of the jaggedness using the left and right edge coordinate values of the printed area and the non-printed area), FIG. 8 is used. explain. FIG. 8 is a flowchart showing the procedure of the process executed by the evaluation value calculation unit 203, and shows the process of S403 described in detail.

In S801, the evaluation value calculation unit 203 obtains an approximate straight line La at the left edge of the print area. In this process, for example, the approximate straight line La is obtained from the (x, y) coordinate value of the left edge coordinate Lp of the print area by using the least squares method or the like.

Here, assuming that the slope of the approximate straight line La is a1 and the intercept is b1, the slope a1 = 0.007 and the intercept b1 = 6.551 can be obtained from the two-dimensional array Lp shown in FIG. 7 (a). As a supplement, FIG. 9A shows an x value corresponding to the y value in the approximate straight line La of the left edge coordinate Lp.

In S802, the evaluation value calculation unit 203 obtains an approximate straight line ra at the right edge of the print area. In this process, for example, the approximate straight line ra is obtained from the (x, y) coordinate value of the right edge coordinate rp of the print area by using the least squares method or the like.

Here, assuming that the slope of the approximate straight line ra is a2 and the intercept is b2, the slope a2 = −0.006 and the intercept b2 = 9.203 can be obtained from the two-dimensional array rp shown in FIG. 7 (b). As a supplement, FIG. 9B shows the x value of the approximate straight line ra corresponding to the y value of the right edge coordinate rp.

In S803, the evaluation value calculation unit 203 calculates the midpoint between the approximate straight lines La and ra in the non-printing area. In FIGS. 7A and 7B, the non-printing area is the variable i = 4, 5, 14, 15, and the midpoint between the approximate straight lines La and ra is obtained in the line indicated by the variable i. For example, when the variable i = 4, La (x, y) = (6.58, 4) from FIG. 9 (a) and ra (x, y) = (9.18, 4) from FIG. 9 (b). Therefore, the (x, y) coordinates of the midpoint are (7.88, 4).

In S803, the calculated midpoint is assigned to the left and right edge coordinates L and r, and is set as two-dimensional arrays L'(FIG. 9 (c)) and r'(FIG. 9 (d)). In this way, the left and right edge coordinates detected in S507 in the print area (that is, the position coordinates along the length direction of the straight line image at the end in the width direction of the straight line) are stored in the two-dimensional arrays L'and r'. Will be done. Further, in the non-printed area, the coordinates of the midpoint of the left and right approximate straight lines calculated from the edge coordinates of the printed area are stored. FIG. 10 shows a schematic diagram in which the two-dimensional array L'is used as (x, y) coordinates and plotted with "○" on the binarized image. Further, in the binarized image, the two broken lines indicate approximate straight lines La and ra.

In S804, the evaluation value calculation unit 203 calculates the evaluation value of the jaggedness using the two-dimensional arrays L'and r'calculated based on the printed area and the non-printed area. As a specific calculation method, after calculating the jaggedness (Raggedness_left, Raggedness_right) of the left and right edges by the following equations (7) and (8), the average of them is calculated as the evaluation value (Raggedness) of the jaggedness (the following equation). (9)).

As shown in the above equations (7) and (8), the jaggedness of the left and right edges is obtained by calculating the standard deviation of the x values of the two-dimensional arrays L'and r'. For clogging, the left and right edges of the straight line are used in the print area, and the midpoint of the left and right approximate straight lines calculated from the edge coordinates of the print area is used as the virtual edge in the non-print area. It is obtained by calculating the standard deviation of the entire combined edge.

Therefore, if the non-printed area exists in the two-dimensional arrays L'and r', the virtual edge is included in the calculation of the standard deviation, and the evaluation value is calculated larger than the case where the non-printed area does not exist. .. For the average value used when calculating the standard deviation, the x values of the approximate straight lines La and ra corresponding to the two-dimensional arrays L'(i) and r'(i) are substituted, but the two-dimensional array L is used. The average value may be obtained from ′ (i) and r ′ (i).

Then, when the processing of S403 (that is, the processing of calculating the evaluation value of the jaggedness using the left and right edge coordinate values of the printed area and the non-printing area) is completed, the image processing apparatus 100 shifts the processing to S404.

As described above, in the present embodiment, a method of detecting a printed area and a non-printed area from a straight line image and calculating an evaluation value of jaggedness based on the detected printed area and non-printed area has been described. ..

By using this method, it is possible to eliminate the discrepancy that the evaluation value is better than the evaluation value of the image in which the line is not interrupted in terms of the evaluation value for the image in which the line that is visually interrupted appears to be jagged. For clogging, even if there is a break in the linear image, it is possible to calculate (provide) an evaluation value of the jaggedness that matches the visual inspection.

<Modification example>
In the first embodiment, the left and right edges of the straight line are used in the print area, and the midpoint of the left and right approximate straight lines calculated from the edge coordinates of the print area is used as the virtual edge in the non-print area in obtaining the evaluation value. Then, the standard deviation of the entire edge including the printed area and the non-printed area was calculated.

However, the virtual edge does not necessarily have to be the midpoint of the left and right approximate straight lines in calculating the standard deviation and obtaining the evaluation value of the jaggedness. Therefore, for example, a coordinate value to be a virtual edge may be set from the edge coordinate value of the adjacent print area, or a uniquely set coordinate value may be set. Further, when a non-printed area is detected in S508, a uniform evaluation value whose value is larger than that of the uninterrupted line may be set.

(Embodiment 2)
In the above-described first embodiment, when there is a break in the straight line, in the above-mentioned prior art, there may be a discrepancy between the visual and the evaluation value regarding the jaggedness of the image. The method of calculating the evaluation value of is explained.

On the other hand, when there is a break in the straight line, there may be a discrepancy between the visual and the evaluation values regarding the density of the image. For example, the density may appear lighter on a line with a break in the visual sense, whereas the density may be higher than that on a line without a break in the evaluation value. Therefore, in the present embodiment, a method of calculating a concentration evaluation value that matches the visual inspection even with a broken line will be described. In the following, the description will be focused on the difference from the above-described first embodiment.

Since the hardware configuration and the functional configuration of the image processing apparatus according to the present embodiment are the same as those of the above-described embodiment, the description thereof will be omitted here. Next, the procedure of the processing executed by the image processing apparatus 100 according to the present embodiment will be described with reference to the flowchart of FIG. 4 described above.

When the processes of S401 and S402 are executed in the same manner as in the first embodiment, in S403, the evaluation value calculation unit 203 calculates an evaluation value indicating the density based on the printed area and the non-printed area detected in S402. The details of the processing of S403 will be described later with reference to FIG.

In S404, the setting unit 204 determines whether or not the evaluation value calculated in S403 satisfies a predetermined condition. Here, it is assumed that two threshold values, large and small, are set, and the setting unit 204 determines whether or not the concentration evaluation value calculated in S403 is outside the range of the two threshold values (clogging is density). Judgment of whether or not to correct). This threshold value may be arbitrarily set by the user. For example, the evaluation result can be prepared as a data group in advance and set based on this data group. Here, the concentration evaluation value shall indicate that the larger the value, the higher the concentration.

Therefore, in the present embodiment, the setting unit 204 determines that the density needs to be image-corrected if the density evaluation value is outside the set threshold value, and shifts the process to S405. Further, the setting unit 204 determines that it is not necessary to change the setting of the image forming apparatus if the density evaluation value is within the set threshold value, and ends the process shown in FIG. Even when one threshold value is set, it can be determined whether or not the setting of the image forming apparatus should be changed depending on whether or not the threshold value is equal to or more than the set threshold value or less than the set threshold value.

In S405, when the setting unit 204 determines in S404 that the setting of the image forming apparatus needs to be changed, the setting unit 204 changes the setting of the image forming apparatus. In particular, in the present embodiment, some examples of setting change processing for correcting the density output by the image forming apparatus 106 will be illustrated. For example, when the density of the linear image is below the threshold range set in S404 and the density is low, the print density of the image forming apparatus 106 can be set to be increased. If the image forming apparatus 106 is an electrophotographic printer, the print density can be increased by increasing the laser output. Further, if the input image data itself can be modified, the density of the image formed by the image forming apparatus 106 can be increased by detecting the line in the image and increasing the pixel value of the pixels constituting the line. it can.

On the contrary, when the density of the linear image exceeds the threshold range set in S404 and the density is high, the print density setting of the image forming apparatus 106 can be set to be lowered. If the image forming apparatus 106 is an electrophotographic printer, the print density can be reduced by reducing the laser output. Further, if the input image data itself can be modified, the density of the image formed by the image forming apparatus 106 can be reduced by detecting the line in the image and reducing the pixel value of the pixels constituting the line. it can.

Whether or not the original data can be modified may be determined by determining whether or not permission is given by user settings or the like. Further, when the setting unit 204 completes the change of the setting of the image forming apparatus in S405, the setting unit 204 ends the process shown in FIG.

<Processing in the evaluation value calculation unit>
Next, the process of S403 executed by the evaluation value calculation unit 203 (that is, the process of calculating the density evaluation value using the left and right edge coordinate values of the printed area and the non-printed area) will be described with reference to FIG. .. FIG. 11 is a flowchart showing the procedure of the process executed by the evaluation value calculation unit 203, and shows the process of S403 described in detail. In the flowchart shown in FIG. 11, the same reference numerals are given to the same processes as those in the first embodiment.

The evaluation value calculation unit 203 obtains the approximate straight line La at the left edge of the print area in S801, and obtains the approximate straight line ra at the right edge of the print area in S802. Calculate the x value.

In FIGS. 7A and 7B, the non-printing areas are variables i = 4, 5, 14, and 15, and the x values of the approximate straight lines La and ra are obtained in the line indicated by the variables i. For example, when the variable i = 4, La (x, y) = (6.58, 4) from FIG. 9 (a) and ra (x, y) = (9.18, 4) from FIG. 9 (b). Is.

In S1103, the x values of the approximate straight lines La and ra calculated are substituted into the left and right edge coordinates L and r, and are used as the two-dimensional arrays L ″ (FIG. 12 (a)) and r ″ (FIG. 12 (b)). Set. In this way, the left and right edge coordinates detected in S507 in the print area are stored in the two-dimensional arrays L ″ and r ″, and the left and right approximate straight lines La calculated from the edge coordinates of the print area in the non-print area. The coordinates of ra are stored.

In S1104, the evaluation value calculation unit 203 calculates the density evaluation value using the two-dimensional arrays L ″ and r ″ calculated based on the printed area and the non-printed area. Hereinafter, the calculation of the density evaluation value of the straight line image will be specifically described.

First, with respect to the luminance image extracted in S501, the region sandwiched between the two-dimensional arrays L ″ and r ″ is defined as Dens_reg. Here, FIG. 13 shows a region of Dens_reg on the luminance image as a schematic diagram. The luminance image shown in FIG. 13 is the same luminance image as the luminance image shown in FIG. 6 (a).

The region painted with the downward-sloping diagonal line pattern shown on the luminance image is shown as the region of Dens_reg, and the two broken lines on the binarized image indicate the approximate straight lines La and ra. From FIG. 13, the area of Dens_reg is the area between the left and right edge coordinates detected in S507 in the print area, and the area between the left and right approximate straight lines calculated from the edge coordinates of the print area in the non-print area.

Next, the density evaluation value is calculated by taking the logarithm of the average pixel value in the Dens_reg region of the luminance image as shown in the following mathematical formula (10).

From FIG. 13, since the region between the approximate straight lines La and ra in the non-printing region is also the density calculation target region, the density evaluation value is calculated small when the non-printing region exists. Therefore, it is possible to eliminate the discrepancy between the visual inspection and the evaluation value, such as the density appearing to be lighter on the line with a break in the visual inspection, but the density is higher than that on the line without the break in the evaluation value.

Then, when the processing of S403 (that is, the processing of calculating the density evaluation value using the left and right edge coordinate values of the printed area and the non-printing area) is completed, the image processing apparatus 100 shifts the processing to S404.

As described above, in the present embodiment, a method of detecting a printed area and a non-printed area from a linear image and calculating a density evaluation value based on the detected printed area and the non-printed area has been described. As a result, even if there is a break in the linear image, it is possible to calculate the density evaluation value that matches the visual observation.

<Modification example>
In the second embodiment, in obtaining the evaluation value, the area between the coordinates of the left and right edges of the straight line is obtained in the print area, and the area between the left and right approximate straight lines calculated from the edge coordinates of the print area is obtained in the non-print area. The density evaluation value was calculated from the brightness value in the combined region. However, it is not always necessary to obtain the density evaluation value as described above. For example, when a print area is detected, a uniform evaluation value having a value larger than that of an uninterrupted line may be set.

(Embodiment 3)
In the second embodiment described above, a method of calculating a concentration evaluation value that matches the visual inspection even with a broken line has been described. In the present embodiment, a method of calculating an evaluation value indicating the degree of interruption for a line with interruption will be described. In the following, the description will be focused on the difference from the above-described embodiment.

Since the hardware configuration and the functional configuration of the image processing apparatus according to the present embodiment are the same as those of the above-described embodiment, the description thereof will be omitted here. Next, the procedure of the processing executed by the image processing apparatus 100 according to the present embodiment will be described with reference to the flowchart of FIG. 4 described above.

When the processes of S401 and S402 are executed in the same manner as in the first embodiment, in S403, the evaluation value calculation unit 203 calculates an evaluation value indicating the degree of interruption based on the printed area and the non-printed area detected in S402. The details of the processing of S403 will be described later with reference to FIG.

In S404, the setting unit 204 determines whether or not the evaluation value calculated in S403 satisfies a predetermined condition. Here, the setting unit 204 determines whether or not the evaluation value of the degree of interruption calculated in S403 is equal to or higher than a predetermined threshold value. This threshold value may be arbitrarily set by the user. For example, the evaluation result can be prepared as a data group in advance and set based on this data group. Here, it is assumed that the evaluation value of the degree of interruption indicates that the larger the value, the more the interruption points.

Therefore, in the present embodiment, if the evaluation value of the degree of interruption is equal to or greater than the set threshold value, the setting unit 204 determines that it is necessary to change the setting of the image forming apparatus for suppressing the interruption of the line, and processes the image. To S405. Further, the setting unit 204 determines that it is not necessary to change the setting of the image forming apparatus if the evaluation value of the degree of interruption is less than the set threshold value, and ends the process shown in FIG.

In S405, when the setting unit 204 determines in S404 that the setting of the image forming apparatus needs to be changed, the setting unit 204 changes the setting of the image forming apparatus. Regarding the process of changing the setting of the image forming apparatus for suppressing the interruption, the same process as the process described in S405 of the above-described first embodiment may be performed. Further, when the setting unit 204 completes the change of the setting of the image forming apparatus in S405, the setting unit 204 ends the process shown in FIG.

<Processing in the evaluation value calculation unit>
Next, the process of S403 executed by the evaluation value calculation unit 203 (that is, the process of calculating the evaluation value of the degree of interruption from the non-printed area detected in S402) will be described with reference to FIG. FIG. 14 is a flowchart showing the procedure of the process executed by the evaluation value calculation unit 203, and shows the process of S403 described in detail.

In S1401, the evaluation value calculation unit 203 refers to the left and right edge coordinates (here, the left edge coordinate (boundary coordinate) Lnp) of the non-printing area of the straight line image obtained in S508, and the y-value is continuous non-printing. Count the number of regions. For example, in FIG. 7A, since the y values of the two-dimensional array Lnp are 4, 5, 14, and 15, there are two continuous non-printing areas, (4,5) and (14,15). is there.

This can be obtained by calculating Lnp (i + 1,2) -Lnp (i, 2) in the two-dimensional array Lnp and adding "1" to the number of sequences other than "1". .. Then, let np_num be the number of non-printing areas in which the y values obtained here are continuous. Here, it is represented by np_num = 2.

In S1402, when the evaluation value calculation unit 203 counts the number of non-printing areas in which y values are continuous in S1401, the evaluation value of the degree of interruption is derived from the number of non-printing areas. Assuming that the evaluation value of the degree of interruption is Blank, the evaluation value of the degree of interruption is derived as shown in the following equation (11).

Here, the evaluation value (Bank) of the degree of interruption is shown as the number of interruptions in the linear image. It is possible to evaluate how much the linear image is interrupted by this interruption degree evaluation value. Then, when the processing of S403 (that is, the processing of calculating the evaluation value of the degree of interruption from the non-printing area detected in S402) is completed, the image processing apparatus 100 shifts the processing to S404.

As described above, in the present embodiment, the print area and the non-print area are detected from the linear image, and the evaluation value of the degree of interruption is calculated by counting the number of areas in which the detected non-print areas are continuous. I explained how to do it. As a result, when there is a break in the straight line image, it is possible to calculate an evaluation value of the degree of breakage indicating how much the straight line image is broken.

<Modification example>
In the third embodiment, the evaluation value of the degree of interruption was calculated by counting the number of regions in which the non-printed regions are continuous. However, it is not always necessary to obtain the evaluation value of the degree of interruption as described above. For example, in S1401, the length of continuous non-printing areas is obtained in each non-printing area, and the length and number of non-printing areas are determined respectively. It may be calculated by weighting. As a supplement, regarding the length of the non-printing area, in the example shown in FIG. 7A, the continuous non-printing areas are (4,5) and (14,15). Is also "2". Further, when a non-printing area is detected, an evaluation value having a value larger than the evaluation value of the uninterrupted line may be uniformly set.

(Embodiment 4)
In the above-described first to third embodiments, methods for calculating the evaluation value of the jaggedness, the concentration evaluation value, and the evaluation value of the degree of interruption have been described, respectively. However, in the above-described embodiment, an image of a vertical straight line is targeted for evaluation, and when the evaluation is actually performed, the document formed by the image forming apparatus 106 may have scattered recording materials, or the reading apparatus 107 may be used. When scanning a document using it, a straight line image may be obtained at an angle.

Therefore, in the present embodiment, as shown in FIG. 3D, a straight line image other than the vertical direction (that is, a straight line image tilted with respect to the vertical direction) and a small print other than the straight line portion are present. The correction method when various images are input will be described. Here, the vertical straight line image is, for example, the straight line image shown in FIG. 3A described above (that is, the image in which straight lines are shown in the vertical direction of FIG. 3A). It is.).

The hardware configuration and functional configuration of the image processing apparatus according to the present embodiment, and the processing other than the processing of S402 in the flowchart shown in FIG. 4 above are the same as those of the above-described embodiment. Is omitted. Next, the process executed by the detection unit 202 in S402 of the flowchart of FIG. 4 described above will be described with reference to FIG.

<Processing of S402 executed by the detection unit>
FIG. 15 is a flowchart showing the procedure of the process executed by the detection unit 202, and shows the process of S402 described in detail. The flowchart shown in FIG. 15 is obtained by adding the processes of S1503 and S1504 to the flowchart of FIG. 5 (Embodiment 1) described above. Hereinafter, the processing of S1503 and S1504 will be described.

When the binarization process is executed on the luminance image converted in S501 in S502, the detection unit 202 removes the small area area from the image subjected to the binarization process in S1503. More specifically, if the area of a continuous region in the binarized image is less than a predetermined threshold, that region is removed from the binarized image.

As a supplement, the description of the process of S1503 will be supplemented with reference to FIG. FIG. 16 is a schematic diagram illustrating a process executed by the detection unit 202. FIG. 16A is an example of a binarized image, and the binarized image shown in FIG. 16A is an image in which the direction of the straight line is not vertical and includes printing other than the straight line. The image is shown.

In FIG. 16A, when one cell shown in the figure is 1 px (pixels), in S1503, for example, a small area in which the area where the print area is continuous is less than 3 px is excluded from the binarized image. .. As a result, a binarized image as shown in FIG. 16B can be obtained, and printing other than the straight line portion can be ignored (removed). This threshold value may be arbitrarily set by the user, and is set based on, for example, the size of a recording material such as toner.

In S1504, the detection unit 202 derives the slope of the straight line in the binarized image in which small prints other than the straight line portion are removed in S1503, and corrects the straight line in the vertical direction. Specifically, the detection unit 202 first obtains an approximate straight line of the binarized image by the least squares method or the like by using all the coordinates in which the pixel value is "0" in the binarized image. Here, assuming that the slope of the approximate straight line is a3 and the intercept is b3, the angle θ with respect to the vertical direction can be obtained by the following equation (12).

Then, the detection unit 202 corrects the inclination of the straight line of the binarized image so that it is in the vertical direction by rotating the image by the angle θ calculated by the above equation. As described above, according to the image processing apparatus according to the present embodiment, even when a straight line image other than the vertical direction or an image having a small print other than the straight line portion is input, the above is described. It is possible to calculate the evaluation value as shown in the first to third embodiments of the above. The clogging is an accurate evaluation even when the recording material is scattered on the original formed by the image forming apparatus 106 or the linear image is tilted and acquired when the original is read by the scanning apparatus 107. The value can be calculated.

(Other embodiments)
The present invention supplies a program that realizes one or more functions of the above-described embodiment to a system or device via a network or storage medium, and one or more processors in the computer of the system or device reads and executes the program. It can also be realized by the processing to be performed. It can also be realized by a circuit (for example, ASIC) that realizes one or more functions.

Input unit 201
Detection unit 202
Evaluation value calculation unit 203
Setting unit 204

Claims (14)

An acquisition means for acquiring image data obtained by reading a line image recorded by an image forming apparatus based on the recorded data by a reading apparatus, and
A detection means for detecting a printed area and a non-printed area in the line image based on the image data, and
It is provided with a derivation means for deriving an evaluation value for evaluating the reproducibility of a line image recorded based on the recorded data by using the result of performing a predetermined process on the image data corresponding to the non-printed area. An image processing device characterized by the fact that. The image processing apparatus according to claim 1, further comprising a setting means for changing the setting of the image forming apparatus based on the evaluation value. The image processing apparatus according to claim 1 or 2, wherein the detection means detects the printed area and the non-printed area by binarizing the line image of the image data. The derivation means obtains the evaluation value from the approximate straight line set based on the position coordinates of both ends in the width direction of the print area in the line image and the position coordinates of both ends in the non-printing. The image processing apparatus according to claim 3, wherein the image processing apparatus is derived by using the position coordinates of the region. The image processing apparatus according to claim 4, wherein the derivation means sets the position coordinates in the non-printing area as the midpoint of an approximate straight line set based on the position coordinates of both ends. .. 4. The derivation means is characterized in that, as the evaluation value, it is derived from the position coordinates along the length direction of the line image at the end in the width direction and the standard deviation in the position coordinates in the non-printed area. Or the image processing apparatus according to 5. The derivation means derives the evaluation value using the brightness value of the print area in the line image and the brightness value of the non-print area, and the brightness value of the non-print area is in the width direction of the print area. The image processing apparatus according to claim 3, wherein the image processing apparatus is shown as a luminance value of a region between approximate straight lines set based on each of the position coordinates of both ends. The image processing apparatus according to claim 3, wherein the derivation means derives the evaluation value using the number of the non-printed areas in the line image. The derivation means according to claim 8, wherein the evaluation value is derived by obtaining the length of the non-printing area and weighting each of the number and the length of the non-printing area. Image processing equipment. The image processing according to any one of claims 3 to 9, wherein the detection means excludes a print area smaller than a predetermined threshold value in the line image from a target area for detecting the non-print area. apparatus. The image processing apparatus according to any one of claims 3 to 10, wherein the detection means corrects the inclination of the line image to a predetermined inclination. The image processing apparatus according to any one of claims 1 to 11, wherein the recorded data is recorded data for recording a continuous line image. An acquisition step of acquiring image data obtained by reading a line image recorded by an image forming apparatus based on the recorded data by a reading apparatus, and
A detection step for detecting a printed area and a non-printed area in the line image based on the image data, and
It includes a derivation step of deriving an evaluation value for evaluating the reproducibility of a line image recorded based on the recorded data by using the result of performing a predetermined process on the image data corresponding to the non-printed area. An image processing method characterized by that. A program for causing a computer to function as each means of the image processing apparatus according to any one of claims 1 to 12.

Images