JP2006309622A - Image processor, image processing method, image processing program and recording medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To automate mask processing of a document image having a regular form. <P>SOLUTION: This image processor has: the document image 210 that is a processing target; an input part 101 receiving input of a mask image 220 for hiding a partial area of the document image 210; an extraction part 103 extracting a mask area 221 shown by the mask image 220 inputted by the input part 101 to obtain a mask extraction image 230; and a superimposing part 106 superimposing the mask extraction image 230 extracted by the extraction part 103 and the document image 210 to hide the partial area of the document image 210. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an image processing apparatus, an image processing method, an image processing program, and a recording medium that perform mask processing on a part of a document image.

  Personal information such as address, name, and age may be written on a manuscript having a standard format such as a questionnaire. From the standpoint of personal information protection, the personal information is blacked out and redistributed and stored.

  Conventionally, in order to protect the personal information described in these questionnaire forms, the corresponding portions have been manually painted black one by one. In addition, a technique is known in which the work can be reduced to specify the area of the standard form, and the black frame surrounded by the ruled line can be specified as the recognition area without excess or deficiency (see, for example, Patent Document 1 below).

  Also, based on the form image, form definition data with detailed contents including area information of the frame area such as the character entry frame and information about the character entry frame not surrounded by the ruled line, etc. is created to identify the character entry frame. A technique for performing processing and the like with high accuracy is known (for example, see Patent Document 2 below).

Japanese Patent No. 3614253 Japanese Patent Laid-Open No. 2001-12610

  However, in the above-described prior art, the personal information portion is painted black by recognizing (identifying) a character entry frame in which personal information or the like is written or an area within the black frame, and recognizing (identifying) the character entry frame or area. Are painted black (the pixels in the frame are converted). For this reason, it is necessary to process one by one from input of an image to black painting, and there is a problem that the work becomes complicated.

  The present invention is an image processing apparatus capable of automatically performing a process of masking a part in which personal information, confidential information, etc. of a document image having a fixed format are described in order to solve the above-described problems caused by the prior art. An object is to provide an image processing method, an image processing program, and a recording medium.

  In order to solve the above-described problems and achieve the object, an image processing apparatus according to a first aspect of the present invention provides a document image to be processed and a mask image for hiding a part of the document image. An input unit that receives an input; an extraction unit that extracts a mask region indicated by a mask image input by the input unit to obtain a mask extraction image; a mask extraction image extracted by the extraction unit; and the document image Superimposing means for superimposing and concealing a partial area of the document image.

  According to the first aspect of the present invention, it is possible to create a mask extraction image for hiding a partial area (personal information, etc.) of a document image and to superimpose it on the document image. For this reason, if a partial area is specified and an image is input, a document image in which the partial area is masked can be automatically created.

  According to a second aspect of the present invention, there is provided an image processing apparatus according to the first aspect of the present invention, further comprising image discriminating means for discriminating each of the document image input by the input means and the mask image. The extracting means extracts the mask area from the image determined as the mask image by the image determining means to obtain a mask extracted image.

  According to the second aspect of the present invention, it is possible to determine whether the input image is a document image or a mask image. Therefore, the mask area extraction process can be performed only on the image determined to be the mask image.

  According to a third aspect of the present invention, in the image processing apparatus according to the first aspect of the present invention, the extracting unit includes a determining unit that determines, for each pixel, whether the mask image is scanned and masked. Further, the mask extraction image is obtained by extracting the mask region based on the result determined by the determining means.

  According to the third aspect of the present invention, it is possible to determine whether or not to mask each pixel in the mask image. Therefore, only the mask area can be extracted.

  According to a fourth aspect of the present invention, there is provided an image processing apparatus according to the first or third aspect of the present invention, further comprising storage means for storing the mask extracted image extracted by the extracting means, wherein the superimposing means The mask extracted image stored by the storage unit and the document image are overlapped to hide a partial area of the document image.

  According to the fourth aspect of the present invention, the extracted mask extraction image can be stored. Therefore, when masking a document image, the stored mask extracted image can be superimposed.

  An image processing apparatus according to a fifth aspect of the present invention is the image processing apparatus according to the first aspect, further comprising printing means for printing the document image superimposed by the superimposing means.

  According to the fifth aspect of the present invention, it is possible to print out a document image in which the mask extraction images are superimposed. Therefore, a document image in which a part of the document image is masked can be obtained.

  In order to solve the above-described problems and achieve the object, an image processing method according to a sixth aspect of the present invention includes a document image to be processed and a mask image for hiding a part of the document image. An input step for receiving an input; an extraction step for extracting a mask region indicated by the mask image input by the input step to obtain a mask extraction image; a mask extraction image extracted by the extraction step; and the document image. And a superimposing step of concealing a partial area of the document image.

  According to the sixth aspect of the present invention, it is possible to create a mask extraction image that hides a partial area of a document image and to superimpose it on the document image. For this reason, if a partial area is specified and an image is input, a document image in which the partial area is masked can be automatically created.

  An image processing program according to claim 7 causes a computer to execute the image processing method according to claim 6.

  According to the seventh aspect of the present invention, the computer can execute the image processing method according to the sixth aspect.

  According to an eighth aspect of the present invention, there is provided a recording medium that can be read by a computer that records the image processing program according to the seventh aspect.

  According to the eighth aspect of the present invention, since the image processing program according to the seventh aspect is recorded, the program can be read by the computer, and thereby the operation of the seventh aspect can be realized by the computer. Is possible.

  According to the image processing apparatus, the image processing method, the image processing program, and the recording medium according to the present invention, a mask process is automatically performed on a part in which personal information, confidential information, and the like are described in a document image having a fixed format. There is an effect that can be.

  Exemplary embodiments of an image processing apparatus, an image processing method, an image processing program, and a recording medium according to the present invention will be described below in detail with reference to the accompanying drawings.

(Embodiment)
FIG. 1 is an explanatory diagram showing a functional configuration of an image processing apparatus according to an embodiment of the present invention. In FIG. 1, the image processing apparatus 100 includes an input unit 101, an image determination unit 102, an extraction unit 103, a scaling unit 104, a storage unit 105, a superposition unit 106, and an output unit 107. Has been.

  The input unit 101 receives an input of a document in which a predetermined portion is blacked out and one or more originals to be blacked out (hereinafter referred to as “black target document”). Specifically, for example, a blacked original and one or a plurality of black target originals are set in an ADF (Auto Document Feeder), and these originals are read. Here, the blacked original and the black target original will be described. Here, “original” means a state before input, and “image” means a state after the original is input.

  FIG. 2A is an explanatory diagram of an example of an input blacked original (document image). In this embodiment, an example of an image having a specific format such as the document image 210 shown in FIG. 2 will be described. Here, a case where the advance payment code field 211 of the document image 210 is painted black (masked) will be described as an example.

  FIG. 2B is an explanatory diagram of an example of an input black document (mask image). In the mask image 220 in FIG. 2B, the blackened portion indicated by reference numeral 221 corresponds to the advance payment code column 210 shown in FIG. The blacked advance payment code field 221 is used to black out the corresponding part of the document before the user inputs it using magic or the like. As the original to be painted black, a document on which necessary items are already described may be copied and used, or a document copied before describing the necessary items may be used.

  FIG. 2C is an explanatory diagram illustrating a black solid created based on the mask image illustrated in FIG. In FIG. 2-3, the mask extraction image 230 is an image created based on the mask image 220. The mask extraction image 230 is the same size as the document image 210. Here, the position of the black solid 231 in the mask extraction image 230 corresponds to the position of the advance payment code 211 in the document image 210. A method for creating the black solid 231 will be described later.

  The image determination unit 102 determines whether the image received by the input unit 101 is a mask image 220 or a document image 210. Specifically, for example, the first read image of the input document is determined as the mask image 220, and the second and subsequent images are determined as the document image 210. In addition, for example, a barcode may be attached to the document, and the type of the document (or image) may be determined by reading the barcode.

  The extraction unit 103 creates a black solid 231 of the mask extracted image to be superimposed on the document image 210 from the mask image 220. To create the black solid 231, first, the origin (0, 0) of the mask image 220 is used as a reference (hereinafter, coordinates based on the small area are referred to as “starting points”), and n × m (n = m even from the origin). Scan a small area of (good). Then, it is determined whether all pixels included in the small area are black pixels. The extraction unit 103 has such a discrimination function.

  Next, it is determined whether or not all pixels included in the n × m small region starting from (0, 1) are black pixels. In this way, the start point is scanned in the main scanning direction and the sub-scanning direction, and the above-described determination is performed on the small area of n × m. Here, it is determined whether or not all the pixels in the small area are black pixels, but may be determined based on, for example, whether the number of black pixels in the small area is equal to or greater than a predetermined number. Next, details of the extraction process described above will be described with reference to FIG.

  FIG. 3A is an explanatory diagram illustrating a part of an enlarged mask image. In FIG. 3A, reference numeral 300 indicates an enlarged part of the mask image 220, and each square (including both white and black) indicates a pixel. The position of each pixel is indicated by coordinates (k, l) with the pixel 301 as the origin (0, 0). Here, the coordinates of the third pixel 302 in the lateral (right) direction from the origin pixel 301 are (0, 3). The coordinate of the fourth pixel 303 in the vertical (downward) direction from the origin pixel 301 is (4, 0).

  In FIG. 3A, the number of pixels is up to (K, 0) in the vertical direction of the origin and (0, L) in the horizontal direction of the origin, and the total number of pixels is (k + 1) × (l + 1). The method of defining the position of the origin and the coordinates of the image is not limited to the above-described method of taking the coordinates, and for example, the coordinates of the origin (0, 0) may be set to the lower right. Further, “−” may be used to represent the coordinates of the pixel.

  Next, the actual black solid extraction process will be described. Here, for the purpose of explaining black solid extraction processing, an image (hereinafter referred to as a “white image”) that is the same as the input mask image 220 (not shown), has the same size and the same number of pixels, and is initialized to all white pixels. Prepare). The white image pixel coordinates are determined in the same manner as the pixel image pixel coordinates of the mask image 220. Then, as described above, a small area of n × m is scanned from the origin of the mask image 220. When all the pixels included in the small area are black pixels, the coordinates of the white image having the same coordinates as the small area are set to black pixels. Further, when all the small areas are not black pixels, no processing is performed. Specific processing will be described below.

  First, the pixel included in the n × m small area is determined from the origin 301 as a starting point. Here, if n and m indicating a small area are n = 2 and m = 2, respectively, and the origin 301 is the starting point, are all the pixels included in the small area as indicated by reference numeral 310 being black pixels? Determine.

  Specifically, the small region 310 starting from the origin 301 includes pixels having coordinates of (0, 0), (0, 1), (1, 0), and (1, 1). Here, the pixels at coordinates (0, 0) and (0, 1) are white pixels, and the pixels at coordinates (1, 0) and (1, 1) are black pixels. Since all the pixels included in the small area 310 are not black pixels, no processing is performed on the coordinates (0,0), (0,1), (1,0), and (1,1) of the white image. Do not (white pixels). Next, scanning is performed in the order of coordinates (0, 1), (0, 2),..., (0, L), and processing is performed for a small region starting from each coordinate. In addition, since the small area starting from these coordinates includes white pixels in any small area, no processing is performed on the white image. Then, when the processing of the coordinates (0, L) is completed, next, the small region starting from the coordinates (1, 0) is determined.

  FIG. 3B is an explanatory diagram illustrating a part of a white image in which a result of determination regarding a small region starting from the coordinates (1, 0) is reflected. In FIG. 3B, reference numeral 320 denotes a part of the white image processed based on the determination result. The pixel 321 is a pixel at the origin (0, 0) of the white image, and the pixel 322 is a pixel at coordinates (1, 0). First, in FIG. 3A, the small region starting from the coordinates (1, 0) includes coordinates (1, 0), (1, 1), (2, 0), and (2, 1). . Since the pixels indicated by these four coordinates are all black pixels, the coordinates (1, 0), (1, 1), (2, 0), and (2, 1) of the white image are converted into black pixels. Next, a small area starting from the coordinates (1, 1) shown in FIG.

  FIG. 3C is an explanatory diagram of a part of a white image that reflects the result of determination on a small region starting from the coordinates (1, 1). In FIG. 3C, reference numeral 330 denotes a part of the white image. The pixel 321 is a pixel at the origin (0, 0), and the pixel 331 is a pixel at coordinates (1, 1). Also, the coordinates (1, 0), (1, 1), (2, 0) and (2, 1) have already been converted to black pixels based on the discrimination result of the small area starting from the coordinates (1, 0). Has been.

  Here, in FIG. 3A, the coordinates (1,1), (1,2), (2,1), and (2,2) are included in the small region starting from the coordinates (1,1). It is. Since the pixels indicated by these four coordinates are all black pixels, the coordinates (1,1), (1,2), (2,1) and (2,2) of the white image are converted into black pixels. Actually, since the coordinates (1, 1) and (1, 2) have already been converted to black pixels, the coordinates (1, 2) and (2, 2) are converted to black pixels. The above processing is repeated up to the coordinates (K, L).

  FIG. 3-4 is an explanatory diagram of a result created by the extraction process for the mask image shown in FIG. 3-1. What is indicated by reference numeral 340 is an enlarged view of a part of the mask extraction image 230. In the example described above, the start point is scanned one pixel at a time to determine the small area, but the start point may be scanned every several pixels to perform the determination process. By performing the discrimination processing by scanning every several pixels, it is possible to speed up the creation of the black solid 231.

  Further, when scanning every several pixels, the number of steps may be different between the main scanning direction and the sub-scanning direction. For example, the processing time can be shortened by reducing the number of steps in the scanning direction to be extracted in detail and making the other scanning direction rough. In the above-described example, the mask image 220 includes handwritten characters and ruled lines. Therefore, n and m of the small area n × m are used as characters and ruled lines so that these characters and ruled lines do not remain. Set to be larger than the line width.

  The scaling unit 104 enlarges / reduces the black solid 231 extracted by the extraction unit 103. For example, when the positions of the blacked original and the black target original are shifted at the time of input and the part to be processed is not completely hidden, the entire part to be processed is hidden by enlarging the black solid 231. Can do. Further, as described above, when the position of the original is shifted and overlaps with an unintended character or ruled line, it can be reduced so that it does not overlap with the character or ruled line. Here, a method of enlarging the black solid 231 will be described.

  4A and 4B are explanatory diagrams illustrating an example of a method for enlarging the black solid. FIG. 4A is a diagram before enlargement, and FIG. 4B is a diagram after enlargement. In FIG. 4A, reference numeral 400 is a part of the mask extraction image 230. There are six black pixels in region 410. These six black pixels form a black solid 231. Moreover, in FIG. 4B, the code | symbol 420 is a part of mask extraction image after expansion. When enlarging the black solid 231, as shown in FIG. 4B, the black solid 231 can be enlarged by painting one pixel around the black pixel in the frame 410.

  Further, the black solid 231 may be enlarged by increasing black pixels in the vertical direction or the horizontal direction. When the black solid 231 is reduced, the black solid 231 can be reduced by a reverse operation when the black solid 231 is enlarged. Specifically, for example, in FIG. 4B, the black solid 231 can be reduced by erasing the outermost black pixel. Further, the black solid 231 may be reduced by reducing the black pixels in the vertical direction or the horizontal direction.

  The storage unit 105 stores the input mask image 220, document image 210, mask extraction image 230, and the like. If the mask extraction image 230 created by the extraction unit 103 is stored, it is not necessary to perform extraction processing from the mask image 220 when masking a part of the same document image 210. In addition, if a plurality of mask extraction images 230 are created and stored in the storage unit 105, a new mask image 220 can be input by using the plurality of mask extraction images 230 even when there are a plurality of portions to be masked. And can be superimposed on the document image 210.

  The superimposing unit 106 superimposes the mask extracted image 230 extracted by the extracting unit 103 on the document image 210. Next, the overlay process of the document image 210 and the mask extraction image 230 will be described.

  FIG. 5 is an explanatory diagram showing the overlay of the document image and the mask extraction image. In FIG. 5, the mask extraction image 230 is superimposed on the document image 210 as a separate layer. By reproducing the color other than the black solid 231 of the mask extraction image 230 as the transmission color, it is possible to read the information of the document image 210 other than the portion where the black solid 231 is superimposed.

  The document image 210 and the mask extraction image 230 may be in a single file format as separate layers, or a single bitmap image may be created. In addition, a file in which information cannot be confirmed by a mask may be created as one file format in which the mask extraction image 230 is overwritten on the document image 210. Here, the created file may be in an image file format or a file format having a layer structure such as PDF (Portable Document Format).

  Next, another example of overlaying the document image 210 and the mask extraction image 230 will be described. First, the smaller one of the values of n and m of n × m indicating the small area described above is obtained. In the following description, it is assumed that n <m. Then, the mask extraction image 230 is OR-compressed to 1 / n, and the document image 210 and the mask extraction image 230 compressed to 1 / n are combined into different layers. At this time, the fact that the resolution of the mask extraction image 230 is 1 / n is recorded in the resolution information header of the image file.

  As described above, since an n × m small area is scanned, there is no dot having a line width less than n pixels. For example, if n = 2, a dot having a line width of one pixel disappears during extraction processing. For this reason, even the smallest image has n dots, so that substantially the same image can be reproduced even if it is reduced to 1 / n. Next, the OR compression will be specifically described.

  FIG. 6A is an explanatory diagram of an example of OR compression. When OR-compressing the mask extraction image 230 to 1 / n, the mask extraction image 230 is divided into n × n meshes. If even one pixel is present in the mesh, the pixel corresponding to the mesh of the reduced image is set as a black pixel. When all the pixels in the mesh are white pixels, the pixel corresponding to the mesh of the reduced image is set as a white pixel.

  Specifically, for example, in FIG. 6A, the mesh 601 includes four pixels. Since these pixels are all white pixels, the pixels corresponding to the mesh of the reduced image are set as white pixels. Since the mesh 602 includes four pixels and includes one black pixel, the pixel corresponding to the mesh of the reduced image is set to a black pixel. By the above processing, an image reduced to 1 / n is created.

  Next, a process for superimposing the document image 210 and the reduced mask extraction image 230 will be described. The document image 210 and the reduced mask extraction image 230 are held as separate layer files. When the document image 210 is printed or displayed, the resolution (1 / n) of the reduced mask extraction image 230 is read from the resolution information header of the image file. Then, the reduced mask extraction image 230 is subjected to resolution conversion processing. Then, the image after the resolution conversion process is superimposed on the document image.

  FIG. 6B is an explanatory diagram of an example of the resolution conversion process. In FIG. 6B, a black pixel 621 is a reduced mask extraction image. The black pixel 621 is subjected to resolution conversion processing based on the resolution read from the resolution information header of the image file. Specifically, when n = 2, an image indicated by reference numeral 622 is obtained. In the case of the white pixel 623, the same processing is performed to obtain an image indicated by reference numeral 624. By the compression processing and resolution conversion processing described above, the file size can be reduced and the mask extraction image 230 can be held.

  The created file can be distributed via a network by e-mail or the like, or can be distributed to a specified folder on a computer connected to the network. Further, by performing the processing as described above by an apparatus such as an MFP (Multi Function Printer), it is possible to obtain a document image 210 in which information cannot be confirmed by a mask while performing the same operation as copying. it can. In addition, since the copying operation is familiar to the user, a user interface that is easy to use for the user can be provided. The output unit 107 outputs the document on which the mask extraction image 230 is superimposed by the overlay processing unit 106. For output, a laser printer or an ink jet printer can be employed.

  In the series of processes from input to output described above, for example, an image read by a scanner can be transmitted to a computer (PC), and an image masked by the PC can be output by a printer. It is also possible to read a document by the MFP, create a document image 210 masked in the MFP, and output it.

  FIG. 7 is an explanatory diagram showing a document image in which mask extracted images are superimposed. In FIG. 7, the information described in the advance payment code 211 column in the document image 210 cannot be confirmed by the black solid 231.

(Processing procedure of image processing apparatus)
Next, an example of a processing procedure of the image processing apparatus 100 according to the embodiment of the present invention will be described. FIG. 8 is a flowchart showing an example of a processing procedure of the image processing apparatus according to the embodiment of the present invention. In the flowchart of FIG. 8, first, an input of an image is received (step S801). Next, the type of image is determined (step S802). Here, the image type is determined by determining whether the input image is the mask image 220 or the document image 210.

  Then, the black solid 231 is extracted from the mask image 220 (step S803), and the mask extraction image 230 is obtained. Then, it is determined whether or not to change the magnification of the black solid 231 (step S804). When the scaling process is not performed (step S804: No), the process proceeds to step S806. On the other hand, when the scaling process is performed (step S804: Yes), the scaling process is performed (step S805). Then, the mask extraction image 231 is superimposed on the document image 210 (step S806), and the document image 210 image is output (step S807). As a result, the series of processes is completed. Next, the black solid 231 extraction process in step S803 will be described.

  FIG. 9 is a flowchart illustrating an example of the black solid extraction processing procedure in step S803. Further, in the flowchart of FIG. 9, the case of performing the discrimination process by scanning the start point pixel by pixel will be described. However, as described above, the discrimination may be performed by scanning the start point every several pixels. In FIG. 8, when the type of image is determined (step S802), first, the vertical coordinate of the pixel coordinate is set to k = 0 (step S901), and the horizontal coordinate is set to l = 0 (step S902). . Next, an n × m small area starting from the coordinates (0, 0) is scanned (step S903), and it is determined whether all the pixels included in the small area are black pixels (step S904).

  When all the pixels included in the small area are black pixels (step S904: Yes), the corresponding pixels in the small area of the white image are set as black pixels (step S905). On the other hand, when all the pixels included in the small area are not black pixels (step S904: No), the process is not performed (step S906), and the process proceeds to step S907. Then, it is determined whether or not the current horizontal coordinate 1 is l = L (step S907).

  If l = L is not satisfied (step S907: No), the current horizontal coordinate l is incremented (step S908), and a small area starting from the next pixel coordinate (k, l) is detected (step S903). ). On the other hand, if l = L (step S907: Yes), it is determined whether the current vertical coordinate k is k = K (step S909).

  When k is not K (step S909: No), the current vertical coordinate k is incremented (step S910), and the horizontal coordinate is set to l = 0 (step S802). On the other hand, when k = K (step S909: Yes), the process proceeds to step S804, and it is determined whether or not the scaling process is performed.

  As described above, according to the image processing apparatus, the image processing method, the image processing program, and the recording medium according to the present invention, mask processing of a part in which personal information, confidential information, and the like are described in a document image having a fixed format Can be performed automatically.

  The image processing method described in the present embodiment can be realized by executing a program prepared in advance on a computer such as a personal computer or a workstation. This program is recorded on a computer-readable recording medium such as a hard disk, a flexible disk, a CD-ROM, an MO, and a DVD, and is executed by being read from the recording medium by the computer. Further, this program may be a transmission medium that can be distributed via a network such as the Internet.

  As described above, the image processing apparatus, the image processing method, the image processing program, and the recording medium according to the present invention are useful for processing a document image having a fixed format, particularly for documents having personal information or confidential information. Is suitable.

It is explanatory drawing which shows the functional structure of the image processing apparatus concerning embodiment of this invention. It is explanatory drawing which shows an example of the input black object original (document image). It is explanatory drawing which shows an example of the inputted black original (mask image). It is explanatory drawing which shows the black solid created based on the mask image shown to FIGS. 2-2. It is explanatory drawing which shows a part of enlarged mask image. It is explanatory drawing which shows a part of white image in which the result discriminate | determined about the small area | region which starts a coordinate (1, 0) was reflected. It is explanatory drawing which shows a part of white image which reflected the result discriminate | determined about the small area | region which uses a coordinate (1, 1) as a starting point. It is the figure produced by the extraction process about the mask image shown to FIGS. It is explanatory drawing (the 1) which shows an example of the method of expanding a black solid. It is explanatory drawing (the 2) which shows an example of the method of expanding a black solid. It is explanatory drawing shown about the superimposition of a document image and a mask extraction image. It is explanatory drawing which shows an example of OR compression. It is explanatory drawing which shows an example of the resolution conversion process. It is explanatory drawing which shows the document image which overlap | superposed the mask extraction image. It is a flowchart which shows an example of the process sequence of the image processing apparatus concerning embodiment of this invention. It is a flowchart which shows an example of the black solid extraction process procedure of step S703.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 Image processing apparatus 101 Input part 102 Image discrimination | determination part 103 Extraction part 104 Scaling part 105 Storage part 106 Superimposition part 107 Output part

Claims (8)

An input means for receiving input of a document image to be processed and a mask image for hiding a part of the document image;
Extraction means for extracting a mask region indicated by the mask image input by the input means to obtain a mask extraction image;
Superimposing means for superimposing the mask extracted image extracted by the extracting means and the document image to hide a part of the document image;
An image processing apparatus comprising: Image discriminating means for discriminating each of the document image inputted by the input means and the mask image;
The image processing apparatus according to claim 1, wherein the extraction unit extracts the mask region from an image determined as a mask image by the image determination unit to obtain a mask extraction image. The extraction unit includes a determination unit that determines, for each pixel, whether the mask image is scanned and masked.
The image processing apparatus according to claim 1, wherein the mask extraction image is obtained by extracting the mask region based on a result determined by the determination unit. Storage means for storing the mask extraction image extracted by the extraction means;
The superimposing unit superimposes the mask extraction image stored in the storage unit and the document image to hide a partial area of the document image. Image processing apparatus.   The image processing apparatus according to claim 1, further comprising a printing unit that prints the document image superimposed by the superimposing unit. An input step for receiving input of a document image to be processed and a mask image for hiding a part of the document image;
An extraction step of extracting a mask region indicated by the mask image input by the input step to obtain a mask extraction image;
A masking image extracted by the extracting step and a superimposing step of superimposing the document image and hiding a part of the document image;
An image processing method comprising:   An image processing program causing a computer to execute the image processing method according to claim 6. A computer-readable recording medium on which the image processing program according to claim 7 is recorded.

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