JP6866107B2 - Image processing equipment, image processing methods, and programs - Google Patents

Description

The present invention relates to a technique for generating print data that can be interpreted by a printing apparatus based on drawing data transmitted from a graphics engine in response to a print instruction from a user.

When printing a document containing characters and thin lines, there are cases where the application sends a drawing command to the printer driver as an image drawing command instead of a text drawing command or a line drawing command. For example, the document may include an image generated by scanning the document or a pattern drawing image represented by a combination of thin lines. Also, when the application applies decoration such as transparency or gradation to characters and thin lines, an image drawing command is sent to the printer driver.

When reducing the characters and thin lines of image attributes in the printer driver, reduction methods such as bilinear, bicubic, and simple thinning (nearest neighbor) are used. Interpolation algorithms such as bilinear and bicubic do not eliminate thin lines when reduced, but lose the sharpness of the edges of characters and thin lines. On the other hand, although sharpness can be maintained by simple thinning, some characters and thin lines may be missing depending on the character font, fine line width, and drawing position.

Therefore, a method has been proposed in which characters and lines are reduced so as not to disappear even with simple thinning (Patent Document 1). In the method described in Patent Document 1, the line of interest is compared with the line immediately preceding it (previous line), and when the data match, the line of interest is thinned out, so that characters and lines are missing due to the reduction process. Is being prevented.

Japanese Unexamined Patent Publication No. 2006-49998

In the method described in Patent Document 1, the thinning process is repeated in a cycle of a predetermined number of lines (for example, every 10 lines), but if the data of the line of interest and the previous line do not match at an early stage in each cycle, the line The number of comparisons increases, which may increase the processing cost. Further, in the method described in Patent Document 1, when comparing the line of interest and the front line, it is determined whether or not they match each pixel, so that the processing cost may be further increased.

Therefore, an object of the present invention is to provide an image processing apparatus, an image processing method, and a program capable of preventing the loss of characters and lines that occur in the image reduction processing by simple thinning at a lower processing cost.

The image processing device according to the present invention is an image processing device that performs line-by-line thinning processing on drawing data generated by an application, and is an acquisition means for acquiring an image area from an image indicated by the drawing data. A determination means for determining whether or not a reduction command has been issued for the image area acquired by the acquisition means, and an acquisition means for determining whether or not the reduction command has been issued by the determination means. A generation means for generating a histogram showing the number of black pixels in each line of an image obtained by binarizing the pixels constituting the image region, a reduction ratio specified by the reduction command, and a histogram generated by the generation means. A candidate line to be thinned out from the image area acquired by the acquisition means is determined based on the above, and the candidate line is thinned out from the image area. The thinning means is provided with the thinning means based on the reduction ratio. The determination means for determining the candidate lines to be thinned out from the image area acquired by the determination means, and the candidate lines determined by the determination means are the lines corresponding to the peaks of the histogram, and the candidate lines have predetermined pixels. A black pixel group in which a number or more of black pixels are continuous is included, and further, white pixels having a predetermined number of pixels or more are continuous in the lines before and after the candidate line so as to be adjacent to the black pixel group. When a pixel group is included, the optimization means includes an optimization means for executing an optimization process of redetermining any of the lines before and after the candidate line as a new candidate line, and the optimization means is the determination means. When any of the lines before and after the candidate line determined by is redetermined as a new candidate line, the line immediately before the candidate line determined by the determination means is continuous with the other candidate lines already determined. When it is determined, the line immediately after the candidate line determined by the determination means is redetermined as a new candidate line .

According to the present invention, it is possible to prevent the loss of characters and lines that occur in the image reduction processing by simple thinning at a lower processing cost.

It is a block diagram which shows an example of the structure of the printing system which concerns on 1st Example. It is a block diagram which shows an example of the hardware composition of the personal computer shown in FIG. It is a block diagram which shows an example of the functional structure of the personal computer shown in FIG. It is a flowchart which shows the reduction process of the drawing image in 1st Embodiment. It is explanatory drawing which shows an example of the drawing image and the histogram generated from the drawing image. It is a flowchart which shows the special thinning-out process in 1st Example. It is a figure for demonstrating the special thinning-out process. It is a flowchart which shows the special thinning-out process in 2nd Example. It is a flowchart which shows the special thinning-out process in 3rd Example. It is explanatory drawing which shows an example of the drawing image of outline character and the histogram generated from the drawing image.

Hereinafter, the first embodiment for carrying out the present invention will be described with reference to the drawings. The configuration shown in the following examples is only an example, and the present invention is not limited to the illustrated configuration.

[Example 1]
FIG. 1 is a block diagram showing an example of the configuration of the printing system according to the first embodiment. The printing system according to this embodiment includes a personal computer (PC) (hereinafter, also referred to as an image processing device) 10 and a printer (hereinafter, also referred to as a printing device) 20. The PC 10 and the printer 20 are connected via LAN1. LAN1 is compatible with the Ethernet communication method. The LAN 1 may be in either a wired or wireless connection form. Further, the PC 10 and the printer 20 may be connected by Bluetooth (registered trademark), USB, or the like instead of LAN1.

FIG. 2 is a block diagram showing an example of the hardware configuration of the PC 10 shown in FIG. As shown in FIG. 2, the PC 10 includes a CPU 101, a RAM 102, a ROM 103, a network I / F 105, a keyboard I / F 106, a display I / F 107, and an external memory I / F 108. Each device is connected by the system bus 104. The PC 10 also includes a keyboard 109, a display 110, and a memory 111. The keyboard 109, the display 110, and the memory 111 may be arranged outside the PC 10.

The CPU 101 comprehensively controls each device connected to the system bus 104 according to the program stored in the RAM 102. The RAM 102 functions as a main memory, a work area, and the like of the CPU 101. The ROM 103 stores various programs and data. The ROM 103 includes a font ROM 103a for storing various fonts, a program ROM 103b for storing a boot program, a BIOS, and the like, and a data ROM 103c for storing various data. In this embodiment, the network I / F 105 is connected to LAN1 and performs communication processing with each device connected to LAN1 such as a printer 20. The keyboard controller I / F 106 controls key input from a keyboard 109 or a pointing device (for example, a mouse) (not shown). The display I / F 107 controls the display processing for the display 110. The external memory I / F 108 controls access to a memory 111 such as a hard disk (HD). The memory 111 stores data 114 including an operating system (OS) 112, software 113 responsible for a printing system, user files, edit files, and the like. In this embodiment, it is assumed that Microsoft Windows (registered trademark) is used as OS112.

FIG. 3 is a block diagram showing an example of the functional configuration of the PC 10 shown in FIG. Application 11 creates a document based on a user's instruction. When the application 11 receives a print instruction for the created document from the user, the application 11 uses the GDI 12 to generate drawing data according to the content of the document. Specifically, when a print instruction is given to the application 11, the application 11 calls a service function group of GDI (Graphics Device Interface). As a result, the GDI 12 issues a GDI drawing command. The printer driver 13 can interpret the drawing data (hereinafter, referred to as "drawing data in GDI format") composed by the GDI drawing command issued by the GDI 12 as print data (so-called PDL (Printer Description Language)) that can be interpreted by the printer 20. Data) and output to the printer 20. In the printer driver 13, a single or a plurality of filters are executed in order. A filter is a unit of printing processing. That is, the output of a certain filter becomes the input of the next connected filter, and each filter is executed in sequence. As a result, PDL data for transmission to the printer 20 is generated. In this embodiment, the printer driver 13 has a layout filter 14 that performs layout processing and a rendering filter 15 that performs rendering processing. The layout filter 14 performs layout processing such as Nup processing on the input GDI function. The Nup process is a process of reducing the logical page of N pages to a physical page of one page and printing it. The rendering filter 15 applies image processing such as enlargement / reduction and rotation to the input drawing data that has undergone layout processing to generate a drawing object and convert it into PDL data. The drawing data reduction process may be executed in advance by the application 11 or may be performed by the printer driver 13. The reduction process in this embodiment is executed by the reduction processing unit 17 included in the rendering filter 15 of the printer driver 13. The port monitor 16 transmits PDL data to the printer 20 via LAN1. Although GDI has been described as an example of the graphics engine here, another graphics engine may be used instead of GDI 12.

Next, the reduction process in the printer driver 13 will be described. FIG. 4 is a flowchart showing a drawing image reduction process according to the first embodiment. FIG. 5 is an explanatory diagram showing an example of a drawing image and a histogram generated from the drawing image. Here, as an example of the reduction process, a drawing image 501 called "Den" shown in FIG. 5A is taken as an example.

In step S401, the reduction processing unit 17 of the rendering filter 15 of the printer driver 13 acquires the drawing images existing in the document for which the print instruction is given via the application 11 one by one. Specifically, the reduction processing unit 17 acquires an image drawing command one by one from the GDI drawing commands issued by the GDI 12. As a result, the area of the image attribute (drawing image) included in the document for which the print instruction is given is acquired. Hereinafter, the drawn image is also referred to as an image area.

In step S402, the reduction processing unit 17 confirms whether or not a reduction command has been given to the drawn image. Specifically, the reduction processing unit 17 confirms whether the reduction command is attached to the image drawing command. If a reduction instruction has been issued, the process proceeds to step S403. On the other hand, if the reduction instruction is not given, the process proceeds to step S408.

In step S403, the reduction processing unit 17 converts the drawing image 501 into a black-and-white binary image. As a binarization method, when the drawing image is an 8-bit grayscale image, the pixel value of the white pixel is 0, and the pixel value of the black pixel is 255, the pixel value of the pixel whose pixel value is less than 255 is There is a method of setting to 0. If the target of the reduction process is not pure black characters or thin lines but characters or thin lines with a certain degree of darkness, binarization with a threshold value corresponding to the desired darkness or Otsu's Binarization according to the binarization algorithm may be applied.

In step S404, the reduction processing unit 17 generates a histogram of the drawing image 501. FIG. 5A shows a drawing image 501 of the character “Den” and a histogram 503 generated in the Y direction thereof. Histogram 503 represents the number of black pixels in each line in the Y direction of the drawing image 501. The reduction processing unit 17 also generates a histogram (not shown) in the X direction of the drawing image 501. Here, the Y direction is a direction corresponding to the sub-scanning direction at the time of document printing. The X direction is a direction corresponding to the main scanning direction at the time of document printing.

In step S405, the reduction processing unit 17 has a thinning optimization target area based on the generated histogram, that is, an area including characters and thin lines that may be missing when the thinning process for each line is applied. Determine if there is. Hereinafter, the thinning optimization target area is also referred to as a character area. For example, looking at the histogram 503, the value (frequency) of the histogram of the Y coordinate smaller than the dashed line 505 and the Y coordinate larger than the dashed line 506 continues to be 0, and the frequency of the Y coordinate sandwiched between the dashed line 505 and the dashed line 506 is. It is 0 or more. As described above, when the line having the frequency of 0 in the histogram continues for more than the preset number of lines (hereinafter referred to as the number of boundary determination lines), it can be determined as the boundary of characters and thin lines. As a result, it is estimated that there are characters and thin lines in the area between the broken line 505 and the broken line 506. The same processing is performed in the X direction, but the description thereof will be omitted here. The area 507 is a thinning optimization target area estimated to have characters and thin lines.

If it is determined that there is a thinning optimization target area (YES in step S405), the reduction processing unit 17 proceeds to the process of step S406. If it is determined that there is no thinning optimization target area (NO in step S405), the reduction processing unit 17 proceeds to the processing of step S407, performs the reduction processing by normal simple thinning, and proceeds to the processing of step S408. .. Here, the normal reduction process by simple thinning is a process of thinning regular lines based on the reduction rate specified by the reduction instruction. The number of characters and thin lines included in the character area differs depending on how many boundary determination lines are set.

In step S406, the reduction processing unit 17 performs a special thinning process on the character area 507, and performs a normal thinning process on the areas other than the character area. Details of the special thinning process in step S406 will be described later with reference to FIG. Then, the process proceeds to step S408.

In step S408, the reduction processing unit 17 determines whether there is another drawing image in the document. If the drawn image exists (YES in step S408), the reduction processing unit 17 returns to the process of step S401 and repeats the processes of steps S401 to S407 for the next drawn image. If there is no drawing image (NO in step S408), the reduction processing unit 17 ends the processing.

Here, the case where one character is included in the drawing image to be reduced is taken as an example, but the drawing image may include a plurality of characters. Further, the above processing can be applied to thin lines other than characters.

Subsequently, the special thinning process in step S406 will be described with reference to FIG. FIG. 6 is a flowchart showing the special thinning process in the first embodiment. FIG. 7 is a diagram for explaining the special thinning process.

In step S601, the reduction processing unit 17 determines a line to be thinned out (hereinafter, referred to as a thinning target line or a candidate line) in the drawing image 501 based on the reduction ratio specified by the reduction instruction. Actually, the coordinates of the thinning target line are calculated. FIG. 7A shows an enlarged view of the character area 507. For example, when the character area 507 is reduced to 2/3, one line is thinned out every three lines. That is, the thinning target line at this time is the line indicated by the diagonal arrow in FIG. 7A. As described above, the normal thinning process is applied to an area other than the character area, that is, an area in the histogram in which lines having a frequency of 0 continue for a predetermined number of lines or more. Therefore, in the following, the description of the processing performed on the area other than the character area 507 in the drawing image 501 will be omitted.

In step S602, the reduction processing unit 17 calculates the size of the block to be processed in the thinning target line determination (determination processing of steps S603 to S605 described later) for determining whether or not the thinning target line should be thinned. In the example shown in FIG. 7A, one line to be thinned out is selected every three lines. However, if the size of the block is 3 lines, the information of the immediately preceding line is required when determining the first line of the block, and the information of the next line is required when determining the third line of the block. become. Therefore, the block used for determining the thinning target line is 5 lines of 3 lines + 2 lines. However, the line actually thinned out in the block is one of the three lines of the thinning target line and the line before and after the thinning target line. In this embodiment, the reduction processing unit 17 applies the subsequent processing in order from the block having the smallest Y coordinate. Further, when the thinning target line is located at the edge of the drawing image, the determination may be made by supplementing the line composed of white pixels.

In the following description, the block 502 in the character area 507 will be the block of interest. The line 701 in the attention block is a thinning target line. Histogram 504 is a histogram of interest corresponding to block 502 of interest.

In step S603, the reduction processing unit 17 determines whether or not the portion corresponding to the line 701 is the peak in the histogram. As a determination method, for example, if the frequency of the thinning target line is the largest in the histogram of interest and the frequency difference between the lines before and after the thinning target line is equal to or greater than a predetermined threshold value, it is regarded as a peak. In this embodiment, when the threshold value of the frequency difference is 10, the attention histogram 504 shows that
Maximum frequency of Y = 18 | (frequency of Y = 18)-(frequency of Y = 17) |> 10
| (Frequency of Y = 18)-(Frequency of Y = 19) |> 10
Will be. Therefore, the reduction processing unit 17 can determine that there is a peak at Y = 18. If it is determined that there is a peak (YES in step S603), the reduction processing unit 17 proceeds to the process of step S604. In the drawing image 501 including the Chinese character "Den" shown in FIG. 5A, there are many horizontal lines and vertical lines, and peaks are likely to appear in the corresponding histograms. However, in the drawing image 508 including the hiragana “nu” shown in FIG. 5 (b), a large peak is not seen in the corresponding histogram 509. Therefore, when the determination in step S603 is made for a part (block) of such a drawing image, it is determined that there is no peak (NO in step S603), and the process proceeds to step S610. In step S610, the reduction processing unit 17 thins out the thinning target line (the line indicated by the diagonal arrow in FIG. 7A) calculated in step S601, and ends the processing.

In step S604, it is determined whether or not there are continuous black pixels in the line (here, line 701) determined to have a peak, which is equal to or greater than the preset number of pixels. Here, the threshold value Th_b of the number of continuous pixels is set to 8, and the line 701 is scanned to search for a black pixel group in which 8 or more black pixels are continuous. Then, the black pixel groups 705 and 706 in which 9 black pixels are continuous are detected. Therefore, the reduction processing unit 17 proceeds to the processing of step S605. The detected information about the black pixel group is stored in the reduction processing unit 17 as black pixel continuous information together with the start coordinates of the black pixel group and the number of consecutive black pixels in the black pixel group. If there is no black pixel group in which black pixels are continuous above the threshold Th_b (NO in step S604), the process proceeds to step S610.

Subsequently, in step S605, the reduction processing unit 17 determines whether or not a white pixel group adjacent to the black pixel group exists in the front and rear lines (lines 703 and 704) of the line 701. Specifically, the reduction processing unit 17 determines whether or not a white pixel group satisfying a preset condition exists in the same X coordinate region as the black pixel group in the front and rear lines of the line 701. FIG. 7B shows an enlarged view of the black pixel group 705 shown in FIG. 7A. Here, in the same X coordinate region as the black pixel group 706, it is determined whether or not there is a white pixel group in which white pixels are continuous at a threshold value Th_w or more. In this embodiment, the threshold Th_w is determined by the following formula.
Threshold Th_w = (number of consecutive black pixels in black pixel group 706 / 2)
In the example shown in FIG. 7B, the white pixel group 707 exists in the same X coordinate region as the black pixel group 706 of the line 703 immediately before the line 701. In the white pixel group 707, 6 white pixels are continuous. Further, the white pixel group 708 exists in the same X coordinate region as the black pixel group 706 of the line 704 immediately after the line 701. In the white pixel group 708, 9 white pixels are continuous. In each of the white pixel groups 707 and 708, since the white pixels are continuous at the threshold value Th_w (= 9/2) or more (YES in step S605), the process proceeds to step S606. If there is no white pixel group in which white pixels are continuous at the threshold Th_w or more in the same X coordinate region as the black pixel group in the lines before and after the line 701 (NO in step S605), the process proceeds to step S610.

In step S606, the reduction processing unit 17 determines from the determination results of steps S603 to S605 that when the thinning target line 701 is thinned out, a part of the characters may be missing. Then, the reduction processing unit 17 determines the thinning target line 701 as the thinning prohibition line, and also determines a new candidate line to be thinned out (hereinafter, also referred to as a next candidate line). The next candidate line is one of the lines before and after the thinning prohibition line (here, lines 703 and 704). As a method of determining which of the lines 703 and 704 is to be thinned out, for example, there is a method of thinning out the line that appears first among the lines 703 and 704 (that is, the line having the smaller Y coordinate). According to this method, line 703 is the target. Further, for example, the histogram frequency difference between the line 703 and the line 711 immediately before the line 703 is compared with the frequency difference between the line 704 and the line 712 immediately after the line 704, and the line having the smaller frequency difference is selected as the next candidate. There is a method of selecting as a line and thinning out. In this method, lines having a similar tendency can be thinned out, so that it becomes easy to leave the shape of characters evenly. Further, for example, when the line 711 immediately before the line 703 appearing earlier in the lines 703 and 704 is thinned out in the block immediately before the block 502, the method of thinning out the line 704 appearing later. There is. As a result, two lines are not thinned out in succession, so that it is possible to prevent the character proportions from collapsing.

If the processing is not completed for all the blocks in step S607 (NO in step S607), the reduction processing unit 17 proceeds to step S609. In step S609, the reduction processing unit 17 determines the next block of interest. Then, the reduction processing unit 17 repeats the processing of steps S603 to S606 for the next attention block. In this embodiment, the next line to be thinned out is the line 709 shown in FIG. 7A, and the next block of interest is the block 710. On the other hand, if the processing is completed for all the blocks (YES in step S607), the reduction processing unit 17 proceeds to the processing in step S608 and determines whether the processing is completed in both the X direction and the Y direction. If it is not completed (NO in step S608), the reduction processing unit 17 returns to the processing of step S601 and performs the processing of steps S601 to S607 in the X direction. If the processing is completed in both the X direction and the Y direction (YES in step S608), the reduction processing unit 17 ends the processing.

As described above, in the present embodiment, in step S601, after the candidate line is determined based on the reduction ratio, the optimization process (the process of steps S602 to S606) is performed to switch the candidate line to a more appropriate line. As a result, it is possible to more reliably prevent the disappearance of characters and thin lines due to simple thinning. Further, in this embodiment, since it is determined whether or not the candidate lines should be thinned out using the histogram, it is not necessary to determine whether or not the candidate lines should be thinned out, and the processing cost can be reduced. it can. Also. Unlike the method described in Patent Document 1, it is not necessary to perform a process of determining whether or not each pixel matches, so that the processing cost can be further reduced.

In this embodiment, a case where processing is performed on dark-density characters and lines in a grayscale image in the flow shown in FIG. 6 is taken as an example. However, processing may be performed on characters and lines drawn using colors such as cyan, magenta, yellow, and black. In addition, processing may be performed on characters and lines drawn in red (Red), green (Green), and blue (Blue). When processing the color image in this way, the color image may be grayscaled and then the same processing as described above may be performed. At that time, it is preferable to use a grayscale conversion formula such as NTSC or sRGB for conversion to a grayscale image.

Further, lines drawn in pure colors such as Cyan, Magenta, Yellow, Black, Red, Green, and Blue may be targeted for thinning processing.

Further, not only the solid line but also the dotted line and the broken line may be processed. For example, when the dotted line or the broken line is included in the processing target, the threshold value used for the determination in step S603 may be set lower than that in the case where only the solid line is the processing target. Further, in the determination in step S604, the ratio of the number of black pixels included in the continuous pixels of a fixed number of pixels (for example, 50% when determining whether or not it is a dotted line) is not the continuous number of black pixels. , It may be determined whether or not it is equal to or higher than a predetermined threshold value.

[Example 2]
In the first embodiment, when there is no peak at the portion corresponding to the thinning target line in the histogram in step S603, an example of thinning the thinning target line in step S610 has been described. In this embodiment, when it is determined in step S603 that there is no peak, the block is divided into smaller parts, and the thinning target line determination is executed again for each part. As a result, the accuracy of the thinning target line determination can be further improved, and the image quality can be further improved.

FIG. 8 is a flowchart showing the special thinning process in the second embodiment. Since the processing of steps S801 to S809 shown in FIG. 8 is the same as the processing of steps S601 to S609 shown in FIG. 6, the description thereof will be omitted. As shown in FIG. 8, in this embodiment, when it is determined that there is no peak in the thinning target line in the process of step S803 (NO in step S803), the process of steps S810 to S815 is executed.

Here, let us take as an example a character area in which three Chinese characters "Den", "Surprising", and "Three" are arranged side by side in the X direction. The number and arrangement of black pixels that make up each of the kanji characters "den," "surprise," and "three" are different. Therefore, there is a possibility that the position of the peak appearing in the histogram generated in the Y direction differs depending on whether the above three kanji are arranged side by side in the character area or when any one of the kanji is arranged. .. Therefore, if the thinning target line is uniformly thinned when NO is determined in step S803, a part of any of the kanji characters may be omitted. Therefore, in this embodiment, in step S810, the reduction processing unit 17 divides the block into smaller regions (parts). As a dividing method, for example, there is a method of generating a histogram in the X direction of the block (the direction of the line to be thinned out) and dividing the block according to the boundary of characters or thin lines specified from the histogram. According to such a method, the blocks can be divided so that the above three Chinese characters belong to different parts. As a result, even when a plurality of characters are lined up as in the above example, it is possible to prevent missing characters.

In step S811, the reduction processing unit 17 performs the same processing as in step S404 for each of the plurality of parts obtained by dividing the parts, and calculates a histogram corresponding to each part. Then, in step S812, the reduction processing unit 17 determines whether or not there is a peak in the thinning target line in the part based on the histogram generated in step S811 for one of the plurality of parts. The process of step S812 is the same as that of step S803. If there is no peak in the thinning target line in the part (NO in step S812), the reduction processing unit 17 proceeds to the process of step S816, thins out the thinning target line, and ends the process. If there is a peak in the thinning target line in the part (YES in step S812), the reduction processing unit 17 proceeds to the process of step S813. In step S813, the same processing as in steps S804 to S806 is performed.

In step S814, the reduction processing unit 17 determines whether or not the processing has been completed for all the parts. If the processing has not been completed for all the parts (NO in step S814), the reduction processing unit 17 proceeds to step S815. In step S815, the next part is determined. Then, the reduction processing unit 17 repeats the processing of steps S810 to S813 for the next part. If the processing for all the parts is completed (YES in step S814), the reduction processing unit 17 proceeds to the processing in step S807.

By the above processing, even when a plurality of characters are included in the drawing image, the thinning process can be applied to each character without missing a part of the characters. Therefore, according to this embodiment, further improvement in image quality can be expected in the thinning process of characters and thin lines. The division method for dividing the block in step S813 is not limited to the above method. For example, the block may be equally divided in the X direction (the direction of the thinning target line). According to such a method, the processing time required for block division can be shortened.

[Example 3]
In this embodiment, when the next candidate line to be thinned out is not found, it is reduced by using an interpolation algorithm such as bilinear or bicubic instead of simple thinning. As a result, the loss of characters and lines is further prevented. The case where there is no next candidate line to be thinned out is, for example, a case where every other line determined to be a peak exists in the attention block. As a specific example, it is conceivable that a white line and a black line are arranged for each line in the block of interest.

The processing of this embodiment will be described with reference to FIG. FIG. 9 is a flowchart showing the special thinning process in the third embodiment. Since the processes of steps S901 to S905 and S909 to S912 shown in FIG. 9 are the same as the processes of steps S601 to S605 and S607 to S610 shown in FIG. 6, the description thereof will be omitted.

As shown in FIG. 9, in the present embodiment, the reduction processing unit 17 determines whether or not there is a next candidate line to be thinned out after the processing in step S905 (step S906). Then, if there is a next candidate line to be thinned out (YES in step S906), the reduction processing unit 17 proceeds to the process of step S907. The process of step S907 is the same as the process of step S606. On the other hand, if there is no next candidate line to be thinned out (NO in step S906), the reduction processing unit 17 proceeds to the process of step S908. In step S908, reduction processing is performed using an interpolation algorithm such as bilinear or bicubic instead of simple thinning. After step S908, the process proceeds to step S909.

By the above processing, for example, even when the white line and the black line are arranged for each line in the attention block as in the above-mentioned example, the image quality (density and hue) in the attention block is not deteriorated. , Can be reduced. Further, for example, even when a complicated character having a large number of strokes is included in the character area, the character proportion can be reduced without breaking the character proportion.

[Example 4]
In the first embodiment, a drawing image in which the background is white and the characters are black, that is, a drawing image of black characters is taken as an example. In this embodiment, a drawing image in which the background is black and the characters are white, that is, a drawing image of outline characters is taken as an example.

FIG. 10 is an explanatory diagram showing an example of a drawing image of outline characters and a histogram generated from the drawing image. The drawing image 1001 shown in FIG. 10 is a black-and-white inverted version of the character area 507 of the drawing image 501 shown in FIG. Therefore, the direction of each peak of the histogram 1003 in the Y direction shown in FIG. 10 is opposite to that of the histogram 503 shown in FIG. 5 (a). In step S603, when the peak is determined for such a drawing image (character area), it may be determined whether the frequency corresponding to the thinning target line is the smallest in the histogram of interest. Further, it may be determined whether or not the frequency difference between the thinning target line and the line before and after the thinning target line is equal to or more than a predetermined threshold value. If YES is determined in both determinations, it can be considered that the thinning target line corresponds to the peak of the histogram. For example, in the attention histogram 1004 of the attention block 1002, it is assumed that Y = 12 is the thinning target line. Then
The minimum frequency of Y = 12 | (Frequency of Y = 12)-(Frequency of Y = 11) |> 10
| (Frequency of Y = 12)-(Frequency of Y = 13) |> 10
If, it is determined that there is a peak at Y = 12. The threshold value of the frequency difference is 10.

In this way, by changing the peak determination condition according to the drawing image, it is possible to reduce the drawing image of outline characters without losing the characters and lines.

(Other Examples)
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.

Claims (11)

An image processing device that performs line-by-line thinning processing on drawing data generated by an application.
An acquisition means for acquiring an image area from the image indicated by the drawing data, and
A determination means for determining whether or not a reduction command has been given to the image area acquired by the acquisition means, and
A histogram showing the number of black pixels in each line of an image obtained by binarizing the pixels constituting the image region acquired by the acquisition means when it is determined by the determination means that the reduction command has been issued. The generation means to generate and
Based on the reduction ratio specified by the reduction instruction and the histogram generated by the generation means, a candidate line to be thinned out from the image area acquired by the acquisition means is determined, and the thinning means for thinning out the candidate line from the image area. ,
Equipped with a,
The thinning means
A determination means for determining a candidate line to be thinned out from the image area acquired by the acquisition means based on the reduction ratio, and a determination means.
The candidate line determined by the determination means is a line corresponding to the peak of the histogram, and the candidate line includes a black pixel group in which black pixels having a predetermined number of pixels or more are continuous, and further. When the lines before and after the candidate line include a white pixel group in which white pixels having a predetermined number of pixels or more are continuous so as to be adjacent to the black pixel group, any of the lines before and after the candidate line. Includes an optimization means that executes an optimization process that redetermines the pixel as a new candidate line.
When the optimization means redetermines any of the lines before and after the candidate line determined by the determination means as a new candidate line, the line immediately before the candidate line determined by the determination means has already been determined. An image processing apparatus, characterized in that, when it is determined that the line is continuous with another candidate line, the line immediately after the candidate line determined by the determination means is redetermined as a new candidate line. An image processing device that performs line-by-line thinning processing on drawing data generated by an application.
An acquisition means for acquiring an image area from the image indicated by the drawing data, and
A determination means for determining whether or not a reduction command has been given to the image area acquired by the acquisition means, and
A histogram showing the number of black pixels in each line of an image obtained by binarizing the pixels constituting the image region acquired by the acquisition means when it is determined by the determination means that the reduction command has been issued. The generation means to generate and
Based on the reduction ratio specified by the reduction instruction and the histogram generated by the generation means, a candidate line to be thinned out from the image area acquired by the acquisition means is determined, and the thinning means for thinning out the candidate line from the image area. ,
With
The thinning means
A determination means for determining a candidate line to be thinned out from the image area acquired by the acquisition means based on the reduction ratio, and a determination means.
The candidate line determined by the determination means is a line corresponding to the peak of the histogram, and the candidate line includes a black pixel group in which black pixels having a predetermined number of pixels or more are continuous, and further. When the lines before and after the candidate line include a white pixel group in which white pixels having a predetermined number of pixels or more are continuous so as to be adjacent to the black pixel group, any of the lines before and after the candidate line. Includes an optimization means that executes an optimization process that redetermines the pixel as a new candidate line.
The optimization means is characterized in that when a region in which lines having a frequency of 0 in the histogram continue for a predetermined number or more is detected, the optimization process is not applied to the detected region. Image processing device. An image processing device that performs line-by-line thinning processing on drawing data generated by an application.
An acquisition means for acquiring an image area from the image indicated by the drawing data, and
A determination means for determining whether or not a reduction command has been given to the image area acquired by the acquisition means, and
A histogram showing the number of black pixels in each line of an image obtained by binarizing the pixels constituting the image region acquired by the acquisition means when it is determined by the determination means that the reduction command has been issued. The generation means to generate and
Based on the reduction ratio specified by the reduction instruction and the histogram generated by the generation means, a candidate line to be thinned out from the image area acquired by the acquisition means is determined, and the thinning means for thinning out the candidate line from the image area. ,
With
The thinning means
A determination means for determining a candidate line to be thinned out from the image area acquired by the acquisition means based on the reduction ratio, and a determination means.
The candidate line determined by the determination means is a line corresponding to the peak of the histogram, and the candidate line includes a black pixel group in which black pixels having a predetermined number of pixels or more are continuous, and further. When the lines before and after the candidate line include a white pixel group in which white pixels having a predetermined number of pixels or more are continuous so as to be adjacent to the black pixel group, any of the lines before and after the candidate line. Includes an optimization means that executes an optimization process that redetermines the pixel as a new candidate line.
The optimization means
The optimization process is executed for each block of the number of lines determined based on the reduction ratio specified by the reduction instruction.
The block contains at least one candidate line determined by the determination means.
When the candidate line determined by the determination means is not the line corresponding to the peak of the histogram, the block including the candidate line determined by the determination means is divided, and the optimization process is performed for each region obtained by the division. An image processing device characterized by performing. An image processing device that performs line-by-line thinning processing on drawing data generated by an application.
An acquisition means for acquiring an image area from the image indicated by the drawing data, and
A determination means for determining whether or not a reduction command has been given to the image area acquired by the acquisition means, and
A histogram showing the number of black pixels in each line of an image obtained by binarizing the pixels constituting the image region acquired by the acquisition means when it is determined by the determination means that the reduction command has been issued. The generation means to generate and
Based on the reduction ratio specified by the reduction instruction and the histogram generated by the generation means, a candidate line to be thinned out from the image area acquired by the acquisition means is determined, and the thinning means for thinning out the candidate line from the image area. ,
With
The thinning means
A determination means for determining a candidate line to be thinned out from the image area acquired by the acquisition means based on the reduction ratio, and a determination means.
The candidate line determined by the determination means is a line corresponding to the peak of the histogram, and the candidate line includes a black pixel group in which black pixels having a predetermined number of pixels or more are continuous, and further. When the lines before and after the candidate line include a white pixel group in which white pixels having a predetermined number of pixels or more are continuous so as to be adjacent to the black pixel group, any of the lines before and after the candidate line. Includes an optimization means that executes an optimization process that redetermines the pixel as a new candidate line.
The optimization means
The optimization process is executed for each block of the number of lines determined based on the reduction ratio specified by the reduction instruction.
The block contains at least one candidate line determined by the determination means.
If any of the lines before and after the candidate line determined by the determination means cannot be determined as a new candidate line, the block including the candidate line determined by the determination means is not thinned out. An image processing device characterized by applying reduction processing. The processing by the thinning means
The image processing apparatus according to any one of claims 1 to 4 , which is executed for each of the Y direction corresponding to the sub-scanning direction at the time of printing and the X direction corresponding to the main scanning direction at the time of printing. .. The generation means
When the image area is a color image, the image area is grayscaled, and the pixels constituting the grayscaled image area are binarized. Any one of claims 1 to 5. The image processing apparatus according to the section. An image processing method that performs line-by-line thinning processing on drawing data generated by an application.
An acquisition step of acquiring an image area from the image indicated by the drawing data, and
A determination step for determining whether or not a reduction command has been given to the acquired image area, and
When it is determined in the determination step that the reduction instruction has been made , a histogram showing the number of black pixels in each line of the image obtained by binarizing the pixels constituting the acquired image region is generated. Generation step and
Based on the reduction ratio specified by the reduction instruction and the histogram generated in the generation step, a candidate line to be thinned out from the acquired image area is determined, and the thinning step of thinning out the candidate line from the image area.
Only including,
The thinning step
Based on the reduction ratio, a determination step of determining a candidate line to be thinned out from the image area acquired in the acquisition step, and a determination step.
The candidate line determined in the determination step is a line corresponding to the peak of the histogram, and the candidate line includes a black pixel group in which black pixels of a predetermined number of pixels or more are continuous, and further. , When the lines before and after the candidate line include a white pixel group in which white pixels having a predetermined number of pixels or more are continuous so as to be adjacent to the black pixel group, the lines before and after the candidate line Includes an optimization step that executes an optimization process that redetermines one as a new candidate line.
In the optimization step, when any of the lines before and after the candidate line determined in the determination step is redetermined as a new candidate line, the line immediately before the candidate line determined in the determination step is determined. An image processing method characterized in that, when it is determined that the line is continuous with another candidate line already determined, the line immediately after the candidate line determined in the determination step is redetermined as a new candidate line. An image processing method that performs line-by-line thinning processing on drawing data generated by an application.
An acquisition step of acquiring an image area from the image indicated by the drawing data, and
A determination step for determining whether or not a reduction command has been given to the acquired image area, and
When it is determined in the determination step that the reduction instruction has been made , a histogram showing the number of black pixels in each line of the image obtained by binarizing the pixels constituting the acquired image region is generated. Generation step and
Based on the reduction ratio specified by the reduction instruction and the histogram generated in the generation step, a candidate line to be thinned out from the acquired image area is determined, and the thinning step of thinning out the candidate line from the image area.
Only including,
The thinning step
Based on the reduction ratio, a determination step of determining a candidate line to be thinned out from the image area acquired in the acquisition step, and a determination step.
The candidate line determined in the determination step is a line corresponding to the peak of the histogram, and the candidate line includes a black pixel group in which black pixels of a predetermined number of pixels or more are continuous, and further. , When the lines before and after the candidate line include a white pixel group in which white pixels having a predetermined number of pixels or more are continuous so as to be adjacent to the black pixel group, the lines before and after the candidate line Includes an optimization step that executes an optimization process that redetermines one as a new candidate line.
In the optimization step, when a region in which the number of lines having a frequency of 0 in the histogram continues for a predetermined number or more is detected, the optimization process is not applied to the detected region. Image processing method. An image processing method that performs line-by-line thinning processing on drawing data generated by an application.
An acquisition step of acquiring an image area from the image indicated by the drawing data, and
A determination step for determining whether or not a reduction command has been given to the acquired image area, and
When it is determined in the determination step that the reduction instruction has been made , a histogram showing the number of black pixels in each line of the image obtained by binarizing the pixels constituting the acquired image region is generated. Generation step and
Based on the reduction ratio specified by the reduction instruction and the histogram generated in the generation step, a candidate line to be thinned out from the acquired image area is determined, and the thinning step of thinning out the candidate line from the image area.
Only including,
The thinning step
Based on the reduction ratio, a determination step of determining a candidate line to be thinned out from the image area acquired in the acquisition step, and a determination step.
The candidate line determined in the determination step is a line corresponding to the peak of the histogram, and the candidate line includes a black pixel group in which black pixels of a predetermined number of pixels or more are continuous, and further. , When the lines before and after the candidate line include a white pixel group in which white pixels having a predetermined number of pixels or more are continuous so as to be adjacent to the black pixel group, the lines before and after the candidate line Includes an optimization step that executes an optimization process that redetermines one as a new candidate line.
In the optimization step,
The optimization process is executed for each block of the number of lines determined based on the reduction ratio specified by the reduction instruction.
The block contains at least one candidate line determined in the determination step.
When the candidate line determined in the determination step is not the line corresponding to the peak of the histogram, the block including the candidate line determined in the determination step is divided, and the optimum region obtained by dividing is divided. An image processing method characterized by executing a conversion process. An image processing method that performs line-by-line thinning processing on drawing data generated by an application.
An acquisition step of acquiring an image area from the image indicated by the drawing data, and
A determination step for determining whether or not a reduction command has been given to the acquired image area, and
When it is determined in the determination step that the reduction instruction has been made , a histogram showing the number of black pixels in each line of the image obtained by binarizing the pixels constituting the acquired image region is generated. Generation step and
Based on the reduction ratio specified by the reduction instruction and the histogram generated in the generation step, a candidate line to be thinned out from the acquired image area is determined, and the thinning step of thinning out the candidate line from the image area.
Only including,
The thinning step
Based on the reduction ratio, a determination step of determining a candidate line to be thinned out from the image area acquired in the acquisition step, and a determination step.
The candidate line determined in the determination step is a line corresponding to the peak of the histogram, and the candidate line includes a black pixel group in which black pixels of a predetermined number of pixels or more are continuous, and further. , When the lines before and after the candidate line include a white pixel group in which white pixels having a predetermined number of pixels or more are continuous so as to be adjacent to the black pixel group, the lines before and after the candidate line Includes an optimization step that executes an optimization process that redetermines one as a new candidate line.
In the optimization step,
The optimization process is executed for each block of the number of lines determined based on the reduction ratio specified by the reduction instruction.
The block contains at least one candidate line determined in the determination step.
If any of the lines before and after the candidate line determined in the determination step cannot be determined as a new candidate line, the block including the candidate line determined in the determination step is not simply thinned out. An image processing method characterized by applying other reduction processing. A program for operating a computer as an image processing device according to any one of claims 1 to 6.

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