JP4631371B2 - Image processing device - Google Patents

Description

  The present invention relates to an image processing apparatus that separates a character part and a picture part from image data and performs predetermined processing.

  Raster image data (hereinafter simply referred to as “image data” unless otherwise distinguished) has many image elements with different properties such as character (text) parts and natural picture parts (design parts). Can be included. Due to the difference in properties of these image elements, it is often preferable to perform different image processing for each image element, for example, compression by a different method is suitable for compression processing.

  Therefore, conventionally, image processing called so-called T / I separation has been researched and developed. Conventionally, as a method of T / I separation, for example, a processing target image is binarized, a continuous region of black pixels is defined, and when the size of the defined region is lower than a predetermined threshold value, the region is included in the region. There is a method of determining that an included black pixel represents a character (Patent Document 1).

In addition, for the area thus determined as the character part, the representative colors of the pixels are determined based on the pixel values included in the area, and the values of the pixels constituting each character are set to the representative colors. Some have further increased the compression rate by setting the value (Patent Document 2).
JP 2003-8909 A (see paragraph 0026) JP 2002-165105 A JP 2002-175532 A

  However, in the above method for determining one color for the entire area determined as the character portion, for example, when the character image is subjected to gradation processing and the character is expressed in multiple colors, the expression is lost. It will be.

  On the other hand, if the character part is not separated when the character is expressed in multiple colors, the effect of the T / I separation process is not sufficiently exhibited, such as a reduction in the compression rate.

  The present invention has been made in view of the above circumstances, and an object thereof is to provide an image processing apparatus capable of performing processing corresponding to a character image expressed in multiple colors.

  The present invention for solving the above-described problems of the conventional example is an image processing apparatus, and defines an area including at least one pixel block determined to be a character from at least a part of image data to be processed. Means, character color number determination means for determining the number of colors of a pixel block included in each area, which is determined as the character, as the number of character colors; Background color number determination means for determining, and information on the number of character colors and the number of background colors obtained by the determination is provided for predetermined image processing.

  Here, as the predetermined process, when the determined number of character colors is equal to or less than a predetermined N colors, the representative color information determined based on the mask image representing the pixel block and the color included in the pixel block When the determined number of character colors exceeds the predetermined N colors and the number of background colors is equal to or less than the predetermined M colors, the mask image representing the pixel block is inverted and a background A mask image representing the portion may be generated, and the mask image representing the background portion and representative color information determined based on the color included in the background may be output.

  Further, when the determined number of character colors exceeds the predetermined N colors and the number of background colors is equal to or less than the predetermined M colors, a process of expanding significant pixels of the mask image representing the pixel block is performed. The mask image after the expansion process is inverted to generate a mask image representing the background portion, and the mask image representing the background portion and the representative color information determined based on the color included in the background are output. It is good as well.

  In addition, an image processing method according to an aspect of the present invention includes a step of defining an area including at least one pixel block determined to be a character from at least a part of image data to be processed, and included in each area And determining the number of colors of the pixel block determined as the character as the number of character colors, and determining the number of colors of the pixels serving as the background portion of each area as the number of background colors. The information on the number of character colors and the number of background colors is used for predetermined image processing.

  Furthermore, a program according to another aspect of the present invention includes a procedure for defining a region including at least one pixel block that is determined to be a character from at least a part of image data to be processed in each computer, and included in each region. And determining the number of colors of the pixel block determined as the character as the number of character colors, and determining the number of colors of the pixels serving as the background portion of each region as the number of background colors, and performing the determination The information on the number of character colors and the number of background colors obtained by the above is used for predetermined image processing.

  As shown in FIG. 1, the image processing apparatus according to the embodiment of the present invention includes a control unit 11, a storage unit 12, an image input unit 13, and an image output unit 14. The control unit 11 operates in accordance with a program stored in the storage unit 12 and performs each image processing described later. The contents of this image processing will be described in detail later.

  The storage unit 12 holds a program executed by the control unit 11. The storage unit 12 also operates as a work memory that stores various data generated during the process of the control unit 11. Specifically, the storage unit 12 can be implemented as a computer-readable recording medium and a device that writes data to or reads data from the recording medium (for example, a hard disk device or a memory device).

  The image input unit 13 is, for example, a scanner, and outputs image data obtained by optically reading a document to the control unit 11. Here, it is assumed that the value of each pixel is expressed in an RGB (red, green, blue) color space in the image data output from the image input unit 13. The image output unit 14 outputs image data in accordance with an instruction input from the control unit 11. For example, the image output unit 14 outputs the image data to an image forming unit (printer or the like) or transmits it to an external device via a network. Is what you do.

  Next, the content of the process of the control part 11 is demonstrated. As functionally shown in FIG. 2, the control unit 11 of the present embodiment sets the image data input from the image input unit 13 as a processing target, and performs predetermined preprocessing on the image data that is the processing target. A pre-processing unit 21 that performs a character image extraction, a character extraction unit 22 that extracts a character image portion, a color number determination unit 23, a representative color determination unit 24, a mask image generation unit 25, a post-processing unit 26, and a formatting unit 27. It is comprised including.

  Hereinafter, each of these parts will be described in detail. The preprocessing unit 21 converts the value of each pixel of the image data (processing target image data) input from the image input unit 13 from RGB to YCbCr (a value composed of luminance and color difference). Specifically, the conversion can be performed using the following equation (1). Here, the value of each component of RGB is assumed to be a value from 0x00 (“0x” indicates a hexadecimal number) to 0xFF. Further, the pre-processing unit 21 may correct the gradation of each pixel value based on the luminance and saturation of the background area. However, the gradation correction process is not always necessary.

  The character extraction unit 22 specifies an area including a pixel block that is determined to be a character from the image data output by the preprocessing unit 21. Specifically, in the present embodiment, the character extraction unit 22 specifies a character portion by layout analysis processing.

  Here, processing contents of the layout analysis processing will be described. As functionally shown in FIG. 3, the character extraction unit 22 includes a binarization processing unit 41, a connected pixel extraction unit 42, a basic rectangle definition unit 43, a first separator detection unit 44, and a row rectangle definition unit 45. A second separator detection unit 46, a character region demarcation unit 47, a noise determination unit 48, and a character part specifying unit 49.

  The binarization processing unit 41 includes partial image data in an area defined by the pattern candidate area definition information among the image data (original image data) expressed in the YCbCr color space output from the preprocessing unit 21. Using (picture candidate part data) as a processing target, the pattern candidate part data that is the processing target is binarized to generate binarized picture candidate part data.

  The connected pixel extraction unit 42 performs a labeling process on the binarized pattern candidate partial data, and includes a plurality of continuous pixels having pixel values that satisfy a predetermined condition (for example, a condition such as a black pixel). A pixel group (connected pixel group) is specified.

  The basic rectangle defining unit 43 defines a rectangle (for example, a rectangle circumscribing the connected pixel group) related to the connected pixel group specified by the connected pixel extracting unit 42 as a basic rectangle, and the basic rectangle coordinate information about each connected pixel group Coordinate information for defining a rectangle) is generated. Then, a unique identifier is issued for each basic rectangle, and the identifier and the coordinate information of the basic rectangle are associated and stored in the storage unit 12 as a basic rectangle database.

  The first separator detection unit 44 scans each pixel one line from the left to the right with the pixel at the upper left end of the candidate pattern data to be processed as the initial position, and then similarly for the next lower line. Each pixel is scanned in the scanning order (that is, raster scanning order). When pixels having pixel values that do not satisfy the predetermined condition in the labeling process (for example, white pixels) continue more than a predetermined horizontal direction threshold value, the continuous pixel portion is determined as the first separator (in the horizontal direction). Detect as. The first separator detection unit 44 specifies information for identifying the first separator detected here (such as the coordinates of the leftmost pixel and the rightmost pixel of the continuous pixel portion, where the coordinates are coordinates on the original image data). Or the local coordinates on the pattern candidate portion data may be generated) and stored in the storage unit 12.

  Further, the first separator detection unit 44 scans each pixel in the raster scan order with the pixel at the upper left end of the pattern candidate partial data to be processed as an initial position, and sets a predetermined condition in the labeling process. When pixels having unsatisfactory pixel values (for example, white pixels) continue more than a predetermined vertical direction threshold value, the continuous pixel portion is detected as the first separator (in the vertical direction). Information for identifying the first separator (the coordinates of the upper end pixel and the lower end pixel of the continuous pixel portion, such as the coordinates may be coordinates on the original image data, or on the pattern candidate portion data. Local coordinates may be generated) and stored in the storage unit 12.

  In these processes, the horizontal direction threshold and the vertical direction threshold can be arbitrarily determined by the user. The horizontal threshold is a threshold for dividing each stage in a multi-column layout, and the vertical threshold is a threshold for separating each line from a document including two or more character strings. In addition to the user setting, the horizontal threshold is a predetermined function value based on the basic rectangle width statistical value (average), and the vertical threshold is based on the basic rectangular height statistical value (average). Each may be determined as a predetermined function value.

  Specifically, the first separator is detected in a state as shown in FIG. In FIG. 4A, as a result of detecting the first separators adjacent to each other, one first separator region (shaded portion) is shown.

  The row rectangle defining unit 45 selects one of the basic rectangles stored in the storage unit 12 as the target basic rectangle. Then, the following processing is performed while sequentially selecting the basic rectangles that have been stored in the storage unit 12 and have not been selected as the target basic rectangle so far as the processing target basic rectangles.

  First, the line rectangle demarcating unit 45 is a vector from the center coordinates of the target basic rectangle (if the coordinate information represents the coordinates of each vertex at the diagonal position, the midpoint coordinates thereof) to the center coordinates of the processing target basic rectangle. Is calculated. Further, the row rectangle defining unit 45 calculates the distance between the target basic rectangle and the processing target basic rectangle from the size of the vector (the square root of the sum of squares of each component). When the calculated distance is equal to or less than a predetermined distance threshold, it is checked whether the calculated vector intersects any of the detected first separators. For this process, a widely known process for checking whether or not two line segments intersect can be used. Here, when the calculated vector does not intersect any of the detected first separators, the identifier of the target basic rectangle is associated with the identifier of the target basic rectangle and stored in the storage unit 12 as a basic rectangle relation database. .

  The row rectangle defining unit 45 performs the above processing while sequentially selecting the basic rectangles stored in the storage unit 12 as the target basic rectangle. Then, a series of basic rectangle groups (which may be plural) are linked and identified with reference to the basic rectangle relation database obtained as a result of this processing, and the basic rectangles included in the specified basic rectangle group A rectangle circumscribing is defined as a row rectangle (for example, FIG. 4B).

  For example, in the basic rectangle relation database, a basic rectangle with an identifier “1” is associated with a basic rectangle with an identifier “2”, and a basic rectangle with an identifier “2” and a basic rectangle with an identifier “3” are associated with each other. If they are associated, the row rectangle defining unit 45 integrates these results and specifies the basic rectangles having the identifiers “1”, “2”, and “3” as a series of basic rectangle groups. Then, from the basic rectangles included in the basic rectangle group, the maximum value and minimum value of the x (horizontal direction) value of the coordinate information are extracted, and similarly the maximum value and minimum value of the y (vertical direction) value are extracted. And extract. Then, a first coordinate that is a set of the extracted minimum value of x and a minimum value of y, and a second coordinate that is a set of the maximum value of x and the maximum value of y are respectively set as upper left coordinates and lower right coordinates. A line rectangle is defined as coordinates. That is, the row rectangle is defined by coordinate information including these two coordinate values.

  The row rectangle defining unit 45 issues a unique identifier for each row rectangle thus defined, and information for identifying each identifier, the coordinate information of the row rectangle, and the basic rectangle group included in the row rectangle (the identifier of each basic rectangle) Are stored in the storage unit 12 as a row rectangle database.

  The second separator detection unit 46 scans each pixel in the raster scan order with the pixel at the upper left corner of the pattern candidate partial data to be processed as the initial position. Then, when pixels having pixel values (for example, black pixels) that satisfy a predetermined condition in the labeling process in the connected pixel extraction unit 42 are continuous more than a predetermined horizontal direction threshold, the continuous pixel portion is (horizontal Information that is detected as the second separator (in the direction) and identifies the second separator (such as the coordinates of the leftmost pixel and the rightmost pixel of the continuous pixel portion, where the coordinates are coordinates on the original image data) Or the local coordinates on the pattern candidate portion data may be generated) and stored in the storage unit 12.

  The second separator detection unit 46 scans each pixel in the raster scan order with the pixel at the upper left corner of the pattern candidate partial data to be processed as an initial position, and performs labeling in the connected pixel extraction unit 42. When pixels having a pixel value satisfying a predetermined condition in processing (for example, black pixels) continue more than a predetermined vertical direction threshold, the continuous pixel portion is detected as a second separator (in the vertical direction). , Information for specifying the second separator (the coordinates of the upper end pixel and the lower end pixel of the continuous pixel portion, such as the coordinates may be coordinates on the original image data, or on the pattern candidate portion data Local coordinates may be generated) and stored in the storage unit 12.

  In these processes, the horizontal direction threshold and the vertical direction threshold can be arbitrarily determined by the user. The horizontal threshold is a threshold for dividing each stage in a multi-column layout, and the vertical threshold is a threshold for separating each line from a document including two or more character strings. In addition to user settings, the horizontal threshold is based on a basic rectangle width statistical value (average), and the vertical threshold is based on a basic rectangle height statistical value (average). Each may be determined as a predetermined function value.

  The character area defining unit 47 selects one of the line rectangles defined by the line rectangle defining unit 45 as the target line rectangle. Then, the character area demarcation unit 47 sequentially performs the next processing while sequentially selecting the row rectangles stored in the storage unit 12 and not selected as the target row rectangle so far as the processing target row rectangle. Do.

  In other words, a line segment connecting the coordinates of each vertex of the target line rectangle and the coordinates of the corresponding vertex of the processing target line rectangle, and a polygonal area defined by each side of the target line rectangle and the processing target line rectangle are generated. Then, it is examined whether or not this polygonal region and the second separator (region) intersect (regions overlap at least partially). For this process, a widely known process for checking whether or not two regions intersect can be used.

  Here, when the polygonal region and the second separator do not intersect, the identifier of the target row rectangle and the identifier of the processing target row rectangle are associated with each other and stored in the storage unit 12 as a row rectangle relation database.

  The character area defining unit 47 performs the above processing while sequentially selecting the row rectangles stored in the storage unit 12 as the target row rectangle. Then, a series of row rectangle groups (which may be plural) related to each other in a chained manner are identified with reference to the row rectangle relation database obtained as a result of this processing, and the row rectangles included in the identified row rectangle group A rectangle circumscribing is defined as a character area.

  For example, in the row rectangle relation database, the row rectangle having the identifier “1” is associated with the row rectangle having the identifier “2”, and the row rectangle having the identifier “2” is associated with the row rectangle having the identifier “3”. If they are associated, the row rectangle defining unit 45 integrates these results and identifies the row rectangles having the identifiers “1”, “2”, and “3” as a series of row rectangle groups. Then, from the row rectangles included in the row rectangle group, the maximum value and the minimum value of the x (horizontal direction) value of the coordinate information are extracted, and similarly the maximum value and the minimum value of the y (vertical direction) value are extracted. And extract. Then, a first coordinate that is a set of the extracted minimum value of x and a minimum value of y, and a second coordinate that is a set of the maximum value of x and the maximum value of y are respectively set as upper left coordinates and lower right coordinates. Define the rectangle of the character area as coordinates. That is, the character area is defined by coordinate information including these two coordinate values.

  The character area defining unit 47 issues unique identifiers for the character areas thus defined, and information for identifying each identifier, the coordinate information of the character area, and the group of line rectangles included in the character area (the identifier of each line rectangle identifier). Are stored in the storage unit 12 as a character area database.

  The noise determination unit 48 performs noise determination processing for confirming whether or not a character is included in each of the character regions defined by the character region definition unit 47. Here, the noise determination processing is related to the first noise determination processing for determining whether or not each row rectangle includes a character based on the number of row rectangles or information indicating the property of each row rectangle, and the row rectangle. Second noise processing for determining whether or not a character is included in the row rectangle based on information on the basic rectangle.

  Specifically, the processing of the noise determination unit 48 is performed as shown in FIG. First, the noise determination unit 48 selects a character region stored in the storage unit 12 that has not yet been selected as a target character region as a target character region (S11). Then, the number of line rectangles included in the target character area is checked to determine whether it is 2 or more (that is, whether the character area is composed of a plurality of lines) (S12). Here, if the number of row rectangles is 2 or more (if Yes), the statistics for testing variation such as the width and height of each row rectangle included in the target character area, and their average and standard deviation Is calculated (S13). Then, based on these statistics, it is compared whether or not the variation in the width and height of each row rectangle is larger than a predetermined threshold (S14). This comparison can be, for example, a comparison as to whether or not the standard deviation exceeds a predetermined threshold value. If it is determined by this processing S14 that the variation is large (in the case of Yes), it is determined that no character is included in the target character region, and the target character region is deleted from the character region database in the storage unit 12. (S15), the process proceeds to S18. These processes from S12 to S15 correspond to a first noise determination process. That is, here, the width and height of each row rectangle and their statistics are used as information representing the properties of the row rectangle.

  On the other hand, if it is determined in the process S14 that the variation is small (in the case of No), an in-line determination process (second noise determination process) is performed on each line rectangle included in the target character area (S16). The specific contents of this process S16 will be described later. Then, based on the ratio of the number of lines determined as noise (no character is included) in this process S16 and the number of line rectangles included in the target character area, the number of lines determined as noise is It is determined whether or not the predetermined ratio is greater than or equal to the number of line rectangles included in the character area (S17). When the ratio is equal to or greater than the predetermined ratio, it is determined that no character is included in the target character area. Then, the process proceeds to process S15.

  In step S17, if the ratio is less than the predetermined ratio, it is checked whether or not there is a character area that is not yet a focused character area in the character area database of the storage unit 12 (S18), and there is an unselected character area. If so, the process returns to step S11 to continue the process. Furthermore, if there is no unselected character area in process S18 (if all the character areas have been processed), the noise determination process is terminated.

  Further, if the number of row rectangles is one in process S12 (if No), the process proceeds to process S16 to continue the process. In this case, it is determined whether or not a character is included in the single line rectangle, and if a character is included (in this case, the ratio of processing S17 is “0”), the target character region includes If it is determined that a character is included and no character is included in the single line rectangle (in this case, the ratio of processing S17 is “1”), the character region of interest does not include the character. It is judged.

  Here, the content of the specific process (2nd noise determination process) in process S16 is demonstrated. In this processing, as shown in FIG. 6, the noise determination unit 48 selects one of the row rectangles to be processed as a target row rectangle (S21), and selects a row rectangle database stored in the storage unit 12. With reference to this, the number of basic rectangles included in the target row rectangle is counted (S22). As a result of the counting, the process branches into a case where the number of basic rectangles is “1”, a case where it is “2”, and a case where it is “3” or more (S23), and the number of basic rectangles is “1”. Is obtained, a list of identifiers of the basic rectangles included in the target line rectangle is acquired, the coordinate information of the basic rectangles included in this list is read from the basic rectangle database of the storage unit 12, and the basic rectangles included in this list are read out. The width and height and the product (that is, the area) are calculated. Then, it is determined whether or not the area is equal to or smaller than a predetermined area threshold (S25). If the area is equal to or smaller than the area threshold, it is determined that no character is included in the target line rectangle, The result is stored in the storage unit 12 (S26). Then, it is checked whether or not there is a row rectangle that has not yet been selected as the target row rectangle (S27). The process returns to S21 and continues. On the other hand, if there is no unselected row rectangle in the process S27, the process is terminated and the process returns to the process of FIG.

  Further, when the count value in the process S22 is “2”, the area of each basic rectangle is calculated, and the distance between these basic rectangles is calculated. The distance between the basic rectangles can be calculated as the distance between the centers of the basic rectangles, for example. Then, it is determined whether the distance is larger than a predetermined distance threshold value or the ratio of the areas of the two basic rectangles is larger than a predetermined area ratio threshold value (S31), and the distance is set to a predetermined distance. If it is larger than the threshold value, or if the ratio of the areas of the two basic rectangles is larger than the predetermined area ratio threshold, the process proceeds to step S26 and (X) the process is continued.

  Furthermore, when the count value in process S22 is “3” or more, it is determined whether or not the count value (number of basic rectangles) exceeds a predetermined maximum number (S32). Determines that no character is included in the target line rectangle, and the process proceeds to step S26 (X). This is in consideration of the fact that it is usually impossible to include more than 100 characters in one line, and may be set as a fixed value or adjusted based on the width of the line of interest rectangle. May be. If the number of basic rectangles does not exceed the predetermined maximum number in step S32, the area of each basic rectangle is further calculated to determine whether the calculated maximum area value exceeds the predetermined maximum area value. Judgment is made (S34). If it is determined that the predetermined maximum area value is exceeded, it is determined that no character is included in the target line rectangle, and the process proceeds to step S26 (X). This maximum area value may also be determined as a fixed value, or may be adjusted based on at least one of the width and height of the target row rectangle (for example, the smaller one of them).

  Further, when it is determined in the process S34 that the predetermined maximum area value is not exceeded, the area ratio of the two basic rectangles related to each combination is further determined for two combinations of the basic rectangles (at least one combination arbitrarily extracted). It is determined whether it is larger than a predetermined area ratio threshold value (S35). If the ratio of the areas of the two basic rectangles is larger than the predetermined area ratio threshold value, the process proceeds to step S26 and the process continues ( X).

  When the ratio of the areas of the two basic rectangles is not larger than the predetermined area ratio threshold value in this process S35, it is determined that the character is included in the target line rectangle, and the determination result is stored in the storage unit 12. Then, the process proceeds to process S27.

  In the process S25, when the area exceeds the area threshold value, and in the process S31, the distance is equal to or smaller than the predetermined distance threshold value, and the ratio of the areas of the two basic rectangles is a predetermined area ratio. If it is less than or equal to the threshold value, the process proceeds to the process S32 (or process S34) and the process is continued.

  Further, in the processing S35, the processing is performed for each combination, but in order to reduce the processing load, for example, the average value (average area) of each basic rectangle, the minimum value (minimum area), the maximum value ( The maximum area) may be calculated, and the average area and the minimum area, the ratio of the average area and the maximum area, or the ratio of the minimum area and the maximum area may be compared with the area ratio threshold value.

  As described above, the noise determination unit 48 reconfirms whether or not each row rectangle truly includes a character based on the properties (area, area ratio, distance, etc.) of the basic rectangle included in each row rectangle. To do.

  The first noise determination process of the noise determination unit 48 is not limited to the example described here. For example, the width and height of each row rectangle is used here as the property of the row rectangle, but using the coordinate information of the row rectangle (statistics such as an average value and standard deviation) together with or instead of these, Also good. According to this, when the positions of the line rectangles included in the character area vary, it is determined that the character area does not include a character (noise), and the character area database in the storage unit 12 is determined. Therefore, the attention character area is deleted.

  The character part specifying unit 49 reads the character area database that has undergone the processing of the noise determination unit 48 from the storage unit 12, and the character area included in the character area database (the coordinate information of the character area itself) or the character area database A black pixel portion (character area coordinate information and bitmap information including a black pixel portion) is specified as a character portion, and information (character portion specifying information) for specifying the character portion is stored in the storage unit 12. The control unit 11 may delete the basic rectangle relationship database and the row rectangle relationship database stored in the storage unit 12 at this time.

  As described above, the character extraction unit 22 in the present embodiment demarcates a character area step by step from a character to a line and from a line to an area, and includes a character string based on the state of the line in the delimited character area. If it is determined that the character string is not included, it is further determined whether the character is included based on the state in the line (character unit). However, the layout processing in the present embodiment is not limited to this, and other well-known layout processing may be used.

  One characteristic of this embodiment is that a character portion is extracted using layout analysis in so-called T / I separation processing. Thereby, the extraction accuracy of the character part can be improved.

  The character extraction unit 22 generates a unique region identifier (hereinafter referred to as label data) for each character part specified by the character part specification unit 49, and delimits the label data and the corresponding character region. Coordinate information (vertex coordinate information and the like) is associated with each other and stored in the storage unit 12 as a character area database.

  The number-of-colors determination unit 23 generates mask image data that specifies the same color portion for each character region stored in the character region database of the storage unit 12.

  As shown in FIG. 7, the color number determination unit 23 in the present embodiment includes a character color number determination unit 51 and a background color number determination unit 52.

  The character color number determination unit 51 refers to the coordinate information of the character area stored in the storage unit 12 and selects the significant pixels (character image) included in the basic rectangle in the target character area while sequentially selecting them as the target character area. The number of character colors is counted based on the pixel value of the original image data corresponding to the pixel block group representing the portion).

  Specifically, the character color number determination unit 51 generates a histogram (occurrence frequency) of values corresponding to significant pixels in the target character area in the original image data. Then, pixel values that appear at a frequency exceeding a predetermined threshold in this histogram are specified, and the number of the specified pixel values (the number of pixel values in the character portion) is counted.

  Similarly, the background color number determination unit 52 counts the number of background colors based on the pixel values of the original image data corresponding to pixels other than the significant pixels included in the target character area. Specifically, the background color number determination unit 52 generates a histogram (occurrence frequency) of pixel values of the original image data corresponding to pixels other than significant pixels in the target character area. Then, pixel values that appear with a frequency exceeding a predetermined threshold in the histogram are specified, and the number of the specified pixel values (the number of pixel values in the background portion) is counted.

  As shown in FIG. 8, the representative color determining unit 24 includes a character representative color determining unit 53 and a background representative color determining unit 54. The character representative color determining unit 53 checks whether or not the character color number determined by the character color number determining unit 51 is equal to or less than a predetermined integer N (for example, N = 1), and the character color number is equal to or less than the predetermined number N. In some cases, the character representative color is determined based on the pixel value of the original image data corresponding to the significant pixel included in the target character area.

  The background representative color determination unit 54 checks whether the background color number determined by the background color number determination unit 52 is a predetermined integer M (for example, M = 1) or less, and the background color number is a predetermined number M or less. In some cases, the background representative color is determined based on the pixel values of the original image data corresponding to pixels other than the significant pixels included in the target character area.

  The representative pixel value determination method in these methods generates a histogram (occurrence frequency) of the target pixel value in the original image data as in the color number determination process, and represents the frequent value in this histogram. What is necessary is just to determine as a pixel value.

  The mask image generation unit 25 checks whether the character color number determined by the character color number determination unit 51 is a predetermined integer N (for example, N = 1) or less, and the character color number is a predetermined number N or less. In this case, a significant pixel portion included in the target character area is extracted as a mask image and output. In this case, information on the character representative color output by the character representative color determining unit 53 is selectively output as the representative color corresponding to the mask image.

  If the number of character colors determined by the character color number determination unit 51 exceeds a predetermined integer N, the number of background colors determined by the background color number determination unit 52 is a predetermined integer M (for example, M = 1). If the number of background colors is equal to or less than a predetermined number M, the mask image is inverted and a mask image representing a portion other than the character image (that is, the background portion) is generated in the target character region. . Then, the mask image generation unit 25 outputs a mask image of the background portion. In this case, information on the character representative color output by the background representative color determination unit 54 is selectively output as a representative color corresponding to the mask image.

  Here, when determining the mask image, the mask image generation unit 25 performs a process of expanding each pixel block (significant pixel) included in the target character area. That is, a pixel adjacent to a significant pixel is a significant pixel. Then, the mask image representing the background portion may be generated by inverting the mask image after the expansion process.

  Each generated mask image is output in association with coordinate information defining a corresponding character area (including pixels corresponding to the mask image).

  The post-processing unit 26 receives the input of the mask image generated by the mask image generation unit 25. Then, the post-processing unit 26 removes (sets to a predetermined value) the pixels specified by the mask image from the original image data. The post-processing unit 26 scans each pixel of the image data after removing the pixel in the raster scan order, and selects it as a target pixel. If the pixel is not a pixel from which the pixel of interest has been removed (a pixel set to the predetermined value), the pixel value of the pixel of interest remains as it is, and the pixel value of the pixel of interest is used as the previous pixel value. Stored in the work memory. If another pixel value is already stored as the previous pixel value, the stored content is overwritten.

  If the pixel of interest is a pixel from which the pixel of interest has been removed, the pixel value of the pixel of interest is set to the stored previous pixel value. As a result, the pixel value of the removed portion becomes the same as the previous pixel value in the raster scan order, and the compression efficiency can be improved in many compression processes. The image data after this processing is stored in the storage unit 12 as background data.

  The format unit 27 generates data for reproducing the original image data based on the background data, the mask image, and the representative color information output in association therewith. For example, this data can be described as PDF (Portable Document Format).

  Specifically, the format unit 27 first describes an instruction to draw background portion data. Then, with respect to each generated mask image, the representative color information and the coordinate information defining the target character area output in relation to the mask image are referred to, and the rectangle inside the target character area is filled with the representative color. Describes the instruction to draw the image. Then, an instruction to extract a corresponding mask image portion (a pixel corresponding to a significant pixel in the mask image) from the rectangular shape drawn by this instruction, and the extracted coordinates of the extracted portion on the background data Transmission composition at the position determined by the information (pixels corresponding to outside significant pixels in the mask image are the pixel values of the background data, and pixels corresponding to significant pixels in the mask image are extracted with the representative color obtained above) And an instruction for a pixel value to be combined).

  Thus, according to the image processing apparatus of the present embodiment, when the image to be processed includes characters expressed in a single color, the character portion is extracted as a mask image (FIG. 9 ( a)). Then, data including the extracted mask image, information indicating the color of the character portion, and background portion data that has been subjected to hole filling processing by removing the mask image portion is generated.

  On the other hand, when the character part included in the image to be processed is expressed in multiple colors such as gradation processing, the number of colors in the background part of the area (character area) including the character part is examined, and the background part If the number of colors is one, a mask image representing the background portion is generated (FIG. 9B). Then, data including the extracted background portion mask image, information indicating the color of the background portion, and background portion data that has been subjected to hole filling processing by removing the mask image portion is generated. That is, in this case, the character portion that is expressed in multiple colors remains included in the background portion data.

  In the description of the present embodiment, the process of generating each mask image is performed for a character area obtained by further concatenating a line rectangle including a character string for one line, but the process may be performed for each line rectangle. Good.

  Further, when both the character part and the background part are expressed in multiple colors, the part may be processed as background part data without performing these processes. In this way, for example, each mask image is run-length compressed, and the background data is compressed with JPEG or the like, thereby improving the compression efficiency.

  As described above, according to the present embodiment, it is possible to perform processing corresponding to a character image expressed in multiple colors.

1 is a configuration block diagram illustrating an example of an image processing apparatus according to an embodiment of the present invention. It is a functional block diagram showing the processing content performed by the control part of the image processing apparatus which concerns on embodiment of this invention. 4 is a functional block diagram illustrating an example of processing contents of a character extraction unit 22. FIG. 5 is an explanatory diagram illustrating a processing example of a character extraction unit 22. FIG. FIG. 10 is a flowchart illustrating a processing example of a character extraction unit 22. FIG. 10 is a flowchart illustrating a processing example of a character extraction unit 22. 6 is a functional block diagram illustrating an example of processing contents of a color number determination unit 23. FIG. 6 is an explanatory diagram illustrating a processing example of a representative color determination unit 24. FIG. It is explanatory drawing showing the example of the mask image produced | generated.

Explanation of symbols

DESCRIPTION OF SYMBOLS 11 Control part, 12 Memory | storage part, 13 Image input part, 14 Image output part, 21 Pre-processing part, 22 Character extraction part, 23 Color number determination part, 24 Representative color determination part, 25 Mask image generation part, 26 Post-processing part , 27 format section, 41 binarization processing section, 42 connected pixel extraction section, 43 basic rectangle definition section, 44 first separator detection section, 45 line rectangle definition section, 46 second separator detection section, 47 character area definition section, 48 noise determination unit, 49 character part identification unit, 51 character color number determination unit, 52 background color number determination unit, 53 character representative color determination unit, 54 background representative color determination unit.

Claims (4)

Means for demarcating a region including at least one pixel block determined as a character from at least a part of image data to be processed;
A character color number determination means for determining the number of colors of the pixel block determined to be the character included in each region as the number of character colors;
A background color number determination means for determining the number of colors of a pixel as a background part of each region as the background color number;
Including
Information on the number of character colors and the number of background colors obtained by the determination is an image processing apparatus that is subjected to predetermined image processing ,
As the predetermined process, when the determined number of character colors is equal to or less than a predetermined N colors, a mask image representing the pixel block and representative color information determined based on a color included in the pixel block are output. ,
If the determined number of character colors exceeds the predetermined N colors and the number of background colors is equal to or less than the predetermined M colors, the mask image representing the pixel block is inverted by inverting the mask image representing the pixel block An image processing apparatus that outputs a mask image representing the background portion and representative color information determined based on a color included in the background . The image processing apparatus according to claim 1 ,
When the determined number of character colors exceeds the predetermined N colors and the number of background colors is equal to or less than the predetermined M colors, a process of expanding significant pixels of the mask image representing the pixel block is performed, Inverting the mask image after the expansion process to generate a mask image representing the background portion, and outputting the mask image representing the background portion and representative color information determined based on the color included in the background A featured image processing apparatus. Defining a region including at least one pixel block determined to be a character from at least a part of the image data to be processed;
A step of determining the number of colors of a pixel block included in each region, which is determined as the character, as the number of character colors;
A step of determining the number of colors of a pixel as a background portion of each region as the number of background colors;
Including
Information on the number of character colors and the number of background colors obtained by the determination is an image processing method used for predetermined image processing ,
As the predetermined process, when the determined number of character colors is equal to or less than a predetermined N colors, a mask image representing the pixel block and representative color information determined based on a color included in the pixel block are output. ,
If the determined number of character colors exceeds the predetermined N colors and the number of background colors is equal to or less than the predetermined M colors, the mask image representing the pixel block is inverted by inverting the mask image representing the pixel block And generating a mask image representing the background portion and representative color information determined based on a color included in the background . The computer,
Means for demarcating a region including at least one pixel block determined as a character from at least a part of image data to be processed;
A character color number determination means for determining the number of colors of the pixel block determined to be the character included in each region as the number of character colors;
A background color number determination means for determining the number of colors of a pixel as a background part of each region as the background color number ;
Function as
Information on the number of character colors and the number of background colors obtained by the determination is a program provided for predetermined image processing ,
As the predetermined process, when the determined number of character colors is equal to or less than a predetermined N colors, a mask image representing the pixel block and representative color information determined based on a color included in the pixel block are output. ,
If the determined number of character colors exceeds the predetermined N colors and the number of background colors is equal to or less than the predetermined M colors, the mask image representing the pixel block is inverted by inverting the mask image representing the pixel block And generating a mask image representing the background portion and representative color information determined based on the color included in the background .

Images