JP4311183B2 - Image processing apparatus and program - Google Patents

Description

The present invention relates to an image processing apparatus and a program for specifying a character part from image data.

  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 T / I separation has been researched and developed. Conventionally, as a method of T / I separation, for example, an image to be processed 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. 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 portion, a representative color is determined for each character portion, and the compression rate is further increased by setting the value of the pixel constituting each character to the value of the representative color. It is increasing.
JP 2003-8909 A (see paragraph 0026) JP 2002-175532 A

  However, in the image data to be subjected to the above conventional image processing method, the value of the pixels constituting the character may vary depending on the characteristics such as the reading method and the encoding method. If the value (representative value) of a simple pixel is calculated, the representative value may differ from the original color due to this variation. This situation applies to line drawings as well.

  The present invention has been made in view of the above circumstances, and provides an image processing apparatus that can be set so that there is no sense of incongruity between the representative colors of characters and line drawings and the colors in the original image data and can achieve high image quality. This is one of its purposes.

The invention according to claim 1 is an image processing apparatus that determines a representative color of a target image area based on a pixel value in the target image area defined in the image data to be processed. Means for determining a representative color candidate value from a region, and a correcting means for correcting the luminance of the determined representative color candidate value to determine a representative color, wherein the correcting means includes the representative color candidate For the luminance component of the value, the output value for the input value from the minimum value MIN to the first threshold value TH1 is the minimum value MIN, and from the second threshold value TH2 (where TH2> TH1) to the maximum value MAX. based on a correction function that the output value is set to be the maximum value MAX, the determined representative color information of the to be subjected to predetermined processing on the image data becomes the processing target Those were. Thereby, it can set so that there may be no sense of incongruity with the representative color of a character and a line drawing, and the color in the original image data, and can achieve high image quality.

  At this time, the correction function may be set such that when the input value is a central value MID between the maximum value and the minimum value, the output value corresponding to this is substantially MID.

  In addition, when the color difference component of the representative color candidate value satisfies a predetermined condition, the correction unit performs correction to reduce the number of gradations related to the luminance component value of the representative color candidate value, and The value may be determined as a representative value.

The predetermined condition is that the color difference components a * and b * of the representative value candidates expressed in the color space of L * a * b are within a predetermined range from the center value of the corresponding color difference component range. It may be a condition.

Furthermore, the present invention for solving the problems of the conventional example described above allows the computer to set a representative color of the target image area based on the pixel value in the target image area defined in the image data to be processed. an image processing program for determining, the computer, the target means for determining a representative color candidate values from the image area, for the determined representative color candidate value, and corrects the luminance, to determine the representative color correction In the correction unit, the output value for the luminance component of the representative color candidate value from the minimum value MIN to the first threshold value TH1 is the minimum value MIN. Based on the correction function set so that the output value from the second threshold value TH2 (where TH2> TH1) to the maximum value MAX is the maximum value MAX. Is corrected, the information of the representative color said determined is obtained by the be subjected to a predetermined processing on the image data becomes the processing target.

  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 the pattern processing, a pattern candidate portion specifying processing unit 22 that specifies a portion that is a candidate for a pattern portion (design candidate portion), a character / line image extraction processing unit 23 that extracts a character / line image, and a layout process. The layout processing unit 24, the same color region separation unit 25, a hole filling processing unit 26, and a compression processing unit 27 are included.

  Hereinafter, each of these parts will be described in detail.

[1. Pre-processing section]
In the preprocessing unit 21, the value of each pixel of the image data (processing target image data) input from the image input unit 13 is converted 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.

[2. Design candidate area identification processing unit]
The pattern candidate portion identification processing unit 22 performs a process of identifying an area estimated as a pattern area from the image data expressed in the YCbCr color space output from the preprocessing unit 21 as a pattern candidate area. Specifically, since there are various processing methods of the pattern candidate portion identification processing unit 22, examples of two typical methods will be described below.

  As shown in FIG. 3A, the pattern candidate portion specifying processing unit 22 includes a binarization processing unit 31, a connected pixel extraction unit 32, a feature amount calculation unit 33, an attribute determination unit 34, and a non-pattern region. The processing unit 35, the background region painting unit 36, and the pattern candidate region creation unit 37 are configured.

  The binarization processing unit 31 copies and stores image data expressed in the YCbCr color space output from the preprocessing unit 21 in the storage unit 12. Then, referring to the value of each pixel of the copied image data (design area specifying image data), the luminance component of the pixel value is compared with a predetermined binarization threshold value, and the luminance component is Pixels above the binarization threshold are black pixels (value “1”), pixels whose luminance components are less than the binarization threshold are white pixels (value “0”), and the pattern area specific image data is binarized. Convert to image data.

  The connected pixel extracting unit 32 extracts a region (connected region) where black pixels are connected from the binary image data. For the extraction of the connected region, a process widely known as a labeling process can be used. When the labeling process is used, each connected area is given a different label identifier and stored in the storage unit 12.

  The feature amount calculation unit 33 calculates a predetermined scale feature amount for each of the connected regions extracted by the connected pixel extraction unit 32. Here, the scale feature amount includes the rectangular area determined in relation to the connected region, the density of black pixels in the rectangle (the number of black pixels in the rectangle divided by the number of all pixels in the rectangle) ) Etc. For example, the feature amount calculation unit 33 performs processing as follows. That is, the feature amount calculation unit 33 defines a rectangle circumscribing each connected region (a circumscribed rectangle) as a related region for each connected region. Specifically, for the circumscribed rectangle, among the pixels included in the connected area, the X coordinate of the pixel with the smallest X coordinate (the leftmost pixel in the image area specific image data) is defined as Xmin, and the Y coordinate is also the smallest. X coordinate and Y coordinate of the one with the largest X coordinate and the one with the largest Y coordinate are set to Ymin. , Xmax and Ymax are defined as rectangles having diagonal lines from (Xmin, Ymin) to (Xmax, Ymax). Then, the area A of the circumscribed rectangle is calculated as (Xmax−Xmin) × (Ymax−Ymin). The area A is equal to the number of all pixels included in the circumscribed rectangle. On the other hand, the feature amount calculation unit 33 counts the number of black pixels in the circumscribed rectangle and divides the number by the number of all the pixels (that is, the value of the area A) to obtain the density D.

  In this way, the feature amount calculation unit 33 uses, for each connected region, the area A (corresponding to the area feature amount) of the circumscribed rectangle and the black pixel density D (corresponding to the density feature amount) as the scale feature of the connected region. Calculated as a quantity. Then, the identifier (for example, label identifier) of each connected area and the scale feature amount are associated with each other and stored in the storage unit 12 as a scale feature amount database.

  The attribute determination unit 34 determines whether each connected region is a pattern candidate region while referring to the scale feature amount database stored in the storage unit 12. As a specific example, the attribute determination unit 34 performs a process based on the premise that a character has a certain size or more and the black pixel density inside the character should be relatively small. That is, an area (small area) less than an area (so-called minimum area) corresponding to the minimum font size (for example, 6 points) used in a general document can be determined as a picture area that does not include characters. By removing these small areas, the character portion can be specified.

  In addition, since the characters are basically composed of lines, even a complex character will not be a black pixel in a certain proportion or more of the pixels in the region. Therefore, even if the rectangle has an area larger than the minimum area, it can be determined that the pattern is a pattern when the proportion of the number of black pixels in the rectangle (that is, the black pixel density) is relatively large.

  Furthermore, in the present embodiment, for example, when the area is equal to or larger than the maximum font size (for example, 24 points) used in a general document (ie, the maximum area), it is basically determined that no character is included. it can. However, such a region may be a diagram (graph etc.) as well as a picture. Therefore, the black pixel density is also used here, and it is determined that the image has a pattern only when the black pixel density is relatively large among rectangles having an area larger than the maximum area. This is because a graph such as a graph is composed of lines, so that the density of black pixels is estimated to be relatively low.

  That is, in the present embodiment, for each connected region, it is determined which of the plurality of classes the area feature amount belongs to, and the area of the density threshold value that is predetermined for each class. The density threshold value related to the class to which the feature quantity belongs is compared with the density feature quantity to generate information (classification information referred to in the present invention) indicating whether or not the pattern is a pattern.

  Specifically, the attribute determination unit 34 of the present embodiment includes a first area threshold value α1 representing the minimum area, a second area threshold value α2 representing the maximum area (where α1 <α2), First and second density threshold values (ρ1, ρ2) are determined in advance, and the determination is performed as follows using these threshold values.

  That is, as shown in FIG. 4, the attribute determination unit 34 selects one of the connected areas not yet selected in this process as a target area from the connected areas included in the scale feature amount database (S1). Then, the scale feature quantity associated with the region of interest is read, and whether or not the area A included in the scale feature quantity is less than the first area threshold value α1 (A <α1 or not). Check (S2). Here, if A <α1, the region of interest is determined as a non-picture region, and the identifier of the region of interest (for example, a label identifier) and the determination result (information indicating that the region is a non-pattern region) are stored in association with each other. It is stored in the unit 12 (S3), and it is checked whether or not there is a connected area not yet selected in this process in the scale feature database (S4). If there is an unselected connected area (if Yes) Then, the process returns to the process S1 to continue the process. Further, if there is no unselected connected region in the process S4 (if No), that is, if the determination is completed for all the connected regions, the process is ended.

  If it is determined in step S2 that A <α1 is not satisfied, whether or not the area A of the attention area exceeds the second area threshold value α2 (whether A> α2) is checked (S5). If A> α2, it is checked whether or not the black pixel density D, which is one of the scale feature quantities of the region of interest, is less than the first density threshold ρ1 (whether D <ρ1) ( S6) If D <ρ1, it is determined that the attention area is a picture area, and an identifier of the attention area (for example, a label identifier) and a result of the determination (information indicating that the area is a picture area) are stored in association with each other. The data is stored in the unit 12 (S7), and the process proceeds to S4 (Y). Furthermore, if D <ρ1 in process S6, the process proceeds to process S3 (X) (that is, it is determined as a non-picture area) and the process is continued.

  In step S5, if A> α2, if not, the black pixel density D, which is one of the scale feature amounts of the region of interest, is less than the second density threshold value ρ2 (D <ρ2). (S8), if D <ρ2, the process proceeds to process S3 (X) (that is, it is determined as a non-picture area), and if D <ρ2, the process proceeds to process S7 ( Z) (that is, it is determined as a picture area) and the processing is continued. The first and second density threshold values ρ1 and ρ2 are determined to be values suitable for extracting line drawings and the like by experiments and values suitable for extracting characters and the like.

  Further, at least one of the area feature amount or the area threshold value may be corrected based on the resolution of the image data to be processed. For example, when the area threshold values α1 and α2 are values set at the resolution r0, when the resolution of the image data to be processed is r, the first area threshold value α1 is set to (r / r0). ) × α1 and the second area threshold value α2 is corrected to (r / r0) × α2.

  The non-design area processing unit 35 refers to the determination result for each connected area that is generated by the attribute determination unit 34 and stored in the storage unit 12, and is determined to be a non-design area in the design area specifying image data. The black pixels included in the connected area are converted into white pixels, and the image area specifying image data in which the non-picture area and the background are white pixels is generated.

  The background area filling unit 36 sets white pixels connected to the boundary of the pattern portion to predetermined values (white, black, etc.) for the pattern area specifying image data in which the non-pattern area and the background are white pixels. Fill with any color other than Here, a process of painting a closed region (inside or outside surrounded by a closed curve) as is widely known is used. The pattern candidate area creation unit 37 sets the color of the pixels that have not been painted with the predetermined value by the background area painting unit 36 to black. A portion set as a black pixel by the pattern candidate area creation unit 37 is handled as a pattern candidate area.

  The operation of the pattern candidate portion specifying processing unit 22 by this small area removal method will be described. Hereinafter, a case where the image data illustrated in FIG. 5A is a processing target will be described as an example. For convenience of illustration, FIG. 5A shows the whole as a diagram, but FIG. 5A shows a photograph portion P, a text portion T, a diagram portion G, and a map. And a plate part M such as Further, in the map M, there are cases where characters or the like partially overlapping with the line segments constituting the map are described (X). For example, letters indicating road names are often shown overlapping other roads.

  The pattern candidate portion specifying processing unit 22 binarizes this (FIG. 5B), extracts connected pixels, and performs a small area removal process based on the feature amount for each connected pixel. Then, the pattern area specifying image data is in a state where the text portion (T) is removed as shown in FIG. In FIG. 5, since the black pixel density of the diagram portion G is relatively high, the diagram portion G remains without being removed. In addition, the characters that overlap the line segment in the map portion M are extracted as connected pixels together with the overlapping line segment. For this reason, the area of the rectangle surrounding the connected pixel is increased, and is not removed as a small region, but remains (X in FIG. 5C).

  The pattern candidate portion specifying processing unit 22 fills the white pixel portion B, which is the background, with a predetermined color (FIG. 5D), and further black pixels other than the portion painted with the predetermined color. And As a method of painting the background part here, use the general paint processing that paints the area that is not partitioned by line segments from the four corners of the image data (upper left, upper right, lower left, lower right corners). Can be taken. Then, the pattern candidate part specifying unit 22 returns the predetermined color part to a white pixel. Then, as shown in FIG. 5 (e), pattern area specifying image data is obtained in which the pattern candidate part is a black pixel and the other part is a white pixel.

  In addition, the pattern candidate portion specifying processing unit 22 converts the black pixel included in the connected region determined as the non-pattern region in the pattern region specifying image data by the non-pattern region processing unit 35 to the white pixel. Expansion and contraction processing may be performed on the specific image data. That is, as shown in FIG. 3B, the processing by the pattern candidate portion specifying processing unit 22 is functionally a binarization processing unit 31, a connected pixel extraction unit 32, a feature amount calculation unit 33, and attribute determination. A part 34, a non-picture area processing part 35, an expansion / contraction part 38, a background area painting part 36, and a pattern candidate area creation part 37 may be included.

  Here, the expansion / contraction unit 38 has the pattern area specifying image data obtained by converting the black pixels included in the connected area determined to be the non-pattern area among the pattern area specifying image data by the non-pattern area processing unit 35 into white pixels. Are sequentially selected as the target pixel.

  Then, the expansion / contraction unit 38 performs processing (expansion) when the pixel of interest is a black pixel if there is at least one black pixel in the vicinity of the pixel of interest (four neighborhoods of upper, lower, left, and right pixels or eight neighborhoods of the surrounding eight pixels). Process) to expand the black pixel portion and select the next pixel of interest. The selection order may be the order in which lines are scanned from top to bottom and the lines are scanned from left to right (so-called raster scan order).

  When the expansion / contraction unit 38 completes the expansion processing for all the pixels, the expansion / contraction unit 38 again starts the contraction processing while sequentially selecting each pixel as a target pixel. In the contraction process, if there is at least one white pixel in the vicinity of the pixel of interest (near 4 or 8), the pixel of interest is set as a white pixel. Then, when the contraction process is completed for all the pixels, the process of the expansion / contraction unit 38 ends.

  In this case, the background area filling unit 36 sets the white pixels in the background part connected to the boundary of the pattern part to a predetermined value (with respect to the pattern area specifying image data processed by the expansion / contraction part 38). Any color other than white or black) will be painted.

  By performing the expansion / contraction process in this manner, the halftone dot region is easily distinguished from the background region and recognized as a pattern region.

  In this embodiment, even if the character part is erroneously determined as a pattern in the process of specifying the pattern area candidate, the character part is further extracted by the layout process performed later, so that the extraction accuracy of the pattern candidate area is relatively high. It can be low.

  In the description so far, the background region filling unit 36 fills the background portion with a predetermined color, but the following may be used instead. That is, when a labeling process is used to extract a connected region, a label (background identification) that is larger than the maximum label value obtained at the time of extraction (for example, a value obtained by adding 1 to the maximum label value). (Label) may be set by replacing the label of the pixel in the background portion. In this case, the pattern candidate area creation unit 37 may generate the pattern area specific image data shown in FIG. 5E by setting the pixels not attached with the background specific label to black pixels.

  The control unit 11 stores coordinate information (hereinafter referred to as “design candidate area definition information”) that defines each of the identified design candidate areas in the storage unit 12.

[3. Character line drawing extraction processing unit]
The character / line drawing extraction processing unit 23 performs processing for extracting a character / line drawing part from the image data expressed in the YCbCr color space output from the preprocessing unit 21. For this processing, for example, processing as disclosed in Patent Document 2 can be used.

  The character / line drawing extraction unit processing unit 23 stores the coordinate information of individual characters and rectangles (character / line drawing circumscribed rectangles) surrounding the line drawing parts in the storage unit 12.

[4. Layout processing section]
The layout processing unit 24 reads, from the storage unit 12, the pattern candidate area defining information generated by the pattern candidate portion specifying processing unit 22 and the coordinate information of the character line drawing circumscribing rectangle generated by the character line drawing extraction processing unit 23.

  The layout processing unit 24 performs layout using different determination conditions for each of the pattern candidate area defined by the pattern candidate area definition information and the character / line drawing area defined by the coordinate information of the circumscribed rectangle of the character / line drawing. Analyze.

  Specifically, in the present embodiment, layout analysis processing is performed in the pattern candidate area defined by the pattern candidate area definition information read from the storage unit 12, and further character portions are extracted from the pattern candidate area. Then, a portion excluding the extracted character portion is defined as a pattern region, and is used for subsequent processing.

  Here, processing contents of the layout analysis processing will be described. As functionally shown in FIG. 6, the layout processing unit 24 includes a binarization processing unit 41, a connected pixel extraction unit 42, a basic rectangle defining unit 43, a first separator detecting unit 44, and a row rectangle defining 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 corner of the pattern candidate partial data to be processed as the initial position, and similarly for the next lower line ( That is, when the pixels having pixel values that do not satisfy the predetermined condition in the labeling process (for example, white pixels) are continuously larger than a predetermined horizontal threshold value, the continuous pixel portion is scanned. Is detected as the first separator (in the horizontal direction), and the information specifying the first separator (the coordinates of the left end pixel and the right end pixel of the continuous pixel portion, such as the coordinates are the 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 first separator detection unit 44 scans the pixels of each pixel one line from the top to the bottom with the pixel at the upper left corner of the pattern candidate partial data to be processed as an initial position, The line is scanned in the same manner, and 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 vertical threshold, the continuous pixel portion is Information that is detected as the first separator (in the vertical direction) and identifies the first separator (the coordinates of the upper end pixel and the lower end pixel of the continuous pixel portion, such as the coordinates here are the coordinates on the original image data). Or local coordinates on the pattern candidate portion data) 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. 7A, as a result of detecting the first separators adjacent to each other, it is shown as one first separator region.

  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.

  That is, a vector is calculated from the center coordinates of the target basic rectangle (in the case where the coordinate information represents the coordinates of each vertex at the diagonal position, the center point coordinates thereof) to the center coordinates of the processing target basic rectangle. 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. If 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. 7B).

  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 one line from the left to the right, using the pixel at the upper left corner of the candidate pattern data to be processed as the initial position, and similarly for the line below ( That is, when scanning is performed in the raster scan order), and pixels having pixel values satisfying a predetermined condition in the labeling process in the connected pixel extraction unit 42 (for example, black pixels) are continuously larger than a predetermined horizontal threshold value. In addition, the continuous pixel portion is detected as a second separator (in the horizontal direction), and information specifying the second separator (the coordinates of the left end pixel and the right end pixel of the continuous pixel portion, etc., where the coordinates are the original The coordinates may be coordinates on the image data, or may be local coordinates on the pattern candidate portion data) and stored in the storage unit 12.

  The second separator detection unit 46 scans the pixels of each pixel one line from the top to the bottom with the pixel at the upper left corner of the pattern candidate partial data to be processed as the initial position, The line is scanned in the same manner, and 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 continuously larger than a predetermined vertical direction threshold value. , Information for detecting the continuous pixel portion as a second separator (in the vertical direction) and specifying the second separator (the coordinates of the upper end pixel and the lower end pixel of the continuous pixel portion, where the coordinates are the original image) The coordinates may be coordinates on the data or may be local coordinates on the pattern candidate portion data) 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.

  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. The character area demarcating unit 47 then 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. 9, the noise determination unit 48 selects one of the row rectangles to be processed as a target row rectangle (S21), and selects the 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 been selected as the target row rectangle (S27). If there is an unselected row rectangle, one of the unselected row rectangles is selected as the target row rectangle. 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 a 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 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 layout processing unit 24 according to the present embodiment demarcates character areas 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. As a result, the character portion included in the pattern candidate region is also extracted by the layout analysis process, and the accuracy of extracting the character portion can be improved.

  On the other hand, the layout processing unit 24 performs a layout analysis process also on a portion (character / line drawing circumscribed rectangle) defined as a character / line drawing. The layout processing unit 24 determines layout frames (including at least rectangles (basic rectangles) circumscribing each character) obtained as a result of the layout analysis processing, and stores information (coordinate information and the like) of these layout frames. 12.

  Note that a line rectangle obtained by relating the basic rectangle in the horizontal or vertical direction may also be defined within the character line drawing circumscribed rectangle, and the coordinate information of the line rectangle may be stored in the storage unit 12 together.

  The layout processing unit 24 of the control unit 11 refers to the character part specifying information stored in the storage unit 12 and the character / line drawing circumscribing rectangle (or the layout frame as a layout processing result thereof), and the image to be processed For the entire data, coordinate information of a rectangular area including characters in the image data is generated. Specifically, the layout processing unit 24 combines the rectangle defined by the coordinate information of the character part specifying information and the rectangle defined by the character / line drawing circumscribing rectangle information (or the layout frame as a result of the layout processing). A character line drawing area is generated. In other words, in the present embodiment, the pattern candidate area and the character / line drawing area are defined separately, and therefore the area specified as the character / line drawing area may exist in the pattern candidate area. For this reason, these areas are combined here to make the overlapping area one character / line drawing area.

  Then, the layout processing unit 24 generates a unique area identifier (hereinafter referred to as label data) for each combined character / line drawing part, and coordinates information (vertex) for defining the label data and the corresponding character / line drawing area. The information is stored in the storage unit 12 as a character / line drawing area database.

[5. Same color area separation unit]
The same color area separation unit 25 performs a process of dividing each of the character / line drawing areas stored in the character / line drawing area database of the storage unit 12 into an area including only the character / line drawing parts of the same color. The same color region separation unit 25 reads the coordinate information of the basic rectangle (rectangle defined from both the pattern candidate region and the character / line drawing region) stored in the storage unit 12 during the layout process. Then, a candidate for a representative value (representative color) is determined among the pixel values included in each basic rectangle defined by the coordinate information in the image data (original image data) to be processed.

  Here, as a representative value candidate determination method, there is a method of calculating a histogram of pixel values in a basic rectangle and determining the median value as a representative value (representative color) candidate. At this time, in consideration of the case where the pixel values in the basic rectangle vary, the histogram is calculated after performing the smoothing process. Here, the smoothing process includes a process of sequentially specifying each pixel in each basic rectangle as a target pixel, and setting an average value of the value of the target pixel and the value of a pixel adjacent thereto as the value of the target pixel.

  In the smoothing process, only the pixels constituting the character in the basic rectangle (for example, a portion that becomes a black pixel by the binarization process) may be selected as the target pixel. In the smoothing process, when calculating the average value, the average value may be calculated with reference to only the values of the pixels constituting the character. This prevents the representative color of the character from being influenced by the background color by referring to the pixel value of the portion other than the character.

One of the characteristic features of the present embodiment is that the representative value candidates determined here are corrected. That is, the same color region separation unit 25 of the present embodiment corrects the luminance of the determined representative value candidate, and determines the corrected value as the representative value. Here, the luminance can be corrected using, for example, a tone curve (correction function) as shown in FIG. The tone curve shown in FIG. 10 is an output value (value after correction, that is, a value determined as a representative value) with respect to an input value (luminance of a representative value candidate before correction) from the minimum value MIN to the first threshold value TH1. Brightness) is the minimum value MIN, and the output value from the second threshold TH2 (where TH2> TH1) to the maximum value MAX is set to the maximum value MAX. The tone curve has a center value MID between the maximum value MAX and the minimum value MIN (for example, when the maximum value is “255” and the minimum value is “0”, the MID is “128”). The output value for this may be set to be substantially MID.

  That is, the same color region separation unit 25 corrects the representative value candidate (represented by YCbCr in the present embodiment) with the tone curve shown in FIG. Luminance (Y ′) is determined, and a value specified by this Y ′ and representative value candidate color difference components Cb and Cr is determined as a representative value.

  If the representative value candidate is expressed in a color space that does not include a luminance component, such as RGB, the above processing is performed after conversion to a value in a color space that includes a luminance component such as L * a * b * or YCbCr. Should be done.

  Further, although only the luminance is corrected here, the color difference component may also be corrected. Specifically, the same color region separation unit 25 performs correction to reduce the number of gradations regarding the luminance component value of the representative color candidate value when each color difference component of the representative value candidate satisfies a predetermined condition, The corrected value may be determined as the representative value.

  Specifically, as shown in FIG. 11, the color difference components (a *, b *) of the representative value candidates expressed in the color space of L * a * b are respectively calculated from the center values of the corresponding color difference component value ranges. When the condition of being within a predetermined range (inside the circle defined by THa and THb in FIG. 11) is satisfied, for example, the luminance component L expressed in 256 gradations is converted to 4 gradations or 8 floors. The tone is reduced to a predetermined gradation such as a tone. In this case, the value of the color difference component may be set to the center value. Here, the predetermined ranges THa and THb for each component may be the same value or different values.

  By this processing, when the character color is gray (including black), a representative value that reproduces the original color of the character color is set. For example, when the character color is black, the color difference component and the luminance component are originally “0”. However, depending on the characteristics of the scanner and the encoding format of the original image data (for example, JPEG), the color difference component may be “ In some cases, the luminance component is not “0” or the luminance component is not “0”. Therefore, by performing the processing relating to the color difference component shown here, the representative value can be set to the original black color.

  As described above, according to the present embodiment, the representative color candidate of the target image area is determined based on the pixel values in the basic rectangle or the row rectangle as the target image area defined in the image data to be processed. Then, the luminance is corrected to determine the representative color.

  Here, after performing the smoothing process, the correction process is performed to determine the representative value. However, after performing the above correction process for each pixel by reversing the process order, A representative value may be determined by performing a smoothing process and calculating a histogram. Although the case of characters has been described here, the same processing is performed for line drawings.

  With this smoothing and correction process, in this embodiment, even if there is a variation in the pixel values that make up a character or line drawing, the influence of the variation is reduced and there is no sense of incongruity with the color of the original image data. A representative color can be determined.

That is, the same color region separation unit 25 determines a representative color for each basic rectangle or circumscribed rectangle (hereinafter referred to as a basic rectangle) of a line drawing, and sets the representative color portion in each basic rectangle to a black pixel. A binarized image in which the part is set as a white pixel is generated. Then, while scanning the binarized image in the raster scan order, the binarized image is subjected to run length compression such as MMR (Modified Modified Read) to generate character / line image compression data. Then, the same color area separation unit 25 associates the determined representative color information (pixel value), coordinate information such as the basic rectangle, and the character / line drawing compressed data related to the basic rectangle, etc., and stores it as character / line drawing plane data. To store. The representative color information may be stored as identifier information (hereinafter referred to as a color tag) representing each pixel value, instead of the pixel value itself.
In addition, when there are a plurality of basic rectangles included in the same row rectangle or character area and the difference in representative color is less than a predetermined value, the plurality of basic rectangles are associated with each other and the same color row rectangle or the same A color character area may be defined.

[6. Hole filling section]
The hole-filling processing unit 26 extracts a region corresponding to the pattern candidate region from the original image data, and detects a pixel of a character (a pixel constituting the character) detected by the processing of the layout processing unit 24 from this region. The pattern partial image data is generated by removing.

  Then, each pixel of the pattern partial image data is scanned in the raster scan order, and if the pixel of interest selected by the scanning is not removed, the pixel value of the pixel of interest remains as it is and the pixel of the pixel of interest The value is stored in the work memory of the storage unit 12 as the previous pixel value. If another pixel value is already stored as the previous pixel value, the stored content is overwritten.

  If the pixel of interest selected by scanning is a removed pixel, the pixel value of the pixel of interest is set to the immediately preceding pixel value stored. 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.

  Then, the pattern partial image data after this processing is performed is stored in the storage unit 12 as pattern plane data.

[7. Compression processing unit]
The compression processing unit 27 performs JPEG compression on the design plane data stored in the storage unit 12 to generate compressed design plane data. In addition, the compression processing unit 27 concatenates the character / line drawing plane data stored in the storage unit 12 and the compressed picture plane data to generate a series of data.

Specifically, this series of data includes PDF (Portable Document).
Format) data. That is, an instruction to generate a bitmap generated by decompressing the compressed picture plane data (a bitmap of the picture plane data), and each character or line drawing included in the character / line drawing plane data is drawn on the bitmap of the picture plane data. PDF data including an instruction to be executed.

  Here, the instruction to draw each character or line drawing included in the character line drawing plane data is to read out the character line drawing compressed data, the representative color information related to this and the coordinate information such as the basic rectangle one by one, For the set of the above, the character line drawing compressed data is expanded to generate a binarized image, the color of the black pixel of the binarized image is set as the representative color, and the basic rectangle etc. on the bitmap of the picture plane data This is an instruction for transparent composition at the position set as the coordinate information. Here, “transparent composition” means that pixels other than black pixels (pixels set as representative colors) in the binarized image are not overwritten, but only pixels set as representative colors are overwritten.

  The compression processing unit 27 stores the generated PDF data in the storage unit 12 or outputs the PDF data to the image output unit 14 to send it to an external device.

[Operation]
Since the image processing apparatus according to the present embodiment has the above-described configuration, it operates as follows. Here, a document including a character portion (T1, T2) as shown in FIG. 12A, a photograph portion (P), and a map portion (M) as a line drawing portion is input from the image input unit 13, and this A case where image data of a document is a processing target will be described as an example. In the example of FIG. 12A, a part (T2) of the character part is superimposed on the photograph part (P). The map portion (M) includes a road map and characters. Here, although shown in black and white for the sake of convenience, the road map and characters in the map portion are actually represented in different colors, and the photograph may be in color.

  The preprocessing unit 21 converts the pixel value of the image data into a value of a predetermined color space (YCbCr). The pattern candidate portion specifying processing unit 22 binarizes the image data (original image data), and generates image data from which the character region (T1) and the diagram (M) are removed by removing the small area. (FIG. 12B). At this time, most of the characters and the road map are removed (may be partially left), but the characters superimposed on the photograph portion are in a state of being directly specified as the pattern candidate portion.

  The character / line drawing extraction processing unit 23 binarizes the original image data and extracts the character / line drawing portion by a method such as specifying a small area portion. At this time, the original image data is divided into a plurality of areas, and a binarization threshold value is adaptively determined for each area obtained by the division (such as the method disclosed in Patent Document 2). By performing binarization, it is possible to extract characters from a colored portion such as a map (FIG. 12C).

  The layout processing unit 24 performs a layout analysis process in the pattern candidate part, and extracts a character part (T2) remaining in the pattern candidate part. The same color region separation unit 25 determines a representative color for the character portion or the diagram portion extracted by the character / line drawing extraction processing unit 23 or the layout processing unit 24. One of the characteristic features of the present embodiment is that the original image data is originally one color due to the reading error in the image input unit 13 and the characteristics of the original image data encoding (for example, mosquito noise in JPEG encoding). In consideration of the fact that a plurality of colors may be mixed in a certain character / line image portion, these pixels are smoothed, and further, a correction is made to make darker portions darker and brighter portions brighter. By performing this correction together with the smoothing process, it is possible to suppress a variation that occurs in the luminance portion due to the smoothing process and to set the representative color of the character or line drawing and the color in the original image data so that there is no discomfort. The color difference component may also be corrected together.

  In this way, the control unit 11 performs coordinate information demarcating the area for each character / line drawing portion (T1, T2, M), information indicating the representative color of the pixel in the area, and the representative color in the area. Character line drawing plane data is generated by combining a compressed image of binary bitmap data specifying a portion to be processed.

  The burial processing unit 26 generates image data obtained by removing the character portion (T2) inherent in the pattern candidate portion (FIG. 12D). Originally, the character portion T2 is white according to the character shape. However, in FIG. 12D, the rectangular portion including the character shape is illustrated as white for easy understanding of the drawing. FIGS. 12D and 12E show only the pattern image portion. Then, the hole filling processing unit 26 sets the value of the removed pixel to the nearest pixel value in the scan line order (the pixel value that has not been removed) (FIG. 12E), and generates the picture plane data. To do.

  The compression processing unit 27 performs JPEG compression on the pattern plane data, generates PDF data in combination with the character line drawing plane data, and outputs this to the image output unit 14. The image output unit 14 outputs the PDF data to an external device.

  Here, the compression processing unit 27 may perform a process of reducing the image size (reduction process) on the design plane data before JPEG compression to further improve the compression rate.

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. It is a functional block diagram showing the example of the processing content of the pattern candidate part specific process part. FIG. 6 is a flowchart illustrating a processing example of an attribute determination unit 34. It is explanatory drawing showing the process example of the pattern candidate part specific process part. 4 is a functional block diagram illustrating an example of processing contents of a layout processing unit 24. FIG. 7 is an explanatory diagram illustrating a processing example of a layout processing unit 24. FIG. FIG. 6 is a flowchart illustrating a processing example of a layout processing unit 24. FIG. 6 is a flowchart illustrating a processing example of a layout processing unit 24. It is explanatory drawing showing the example of the tone curve utilized in the same color area separation part 25. FIG. FIG. 11 is an explanatory diagram illustrating processing conditions for correction processing in the same color region separation unit 25. It is explanatory drawing showing the process example of the image processing apparatus which concerns on embodiment of this invention.

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 Design candidate part specific processing part, 23 Character line drawing extraction processing part, 24 Layout processing part, 25 Same color area separation part, 26 burial processing unit, 27 compression processing unit, 31, 41 binarization processing unit, 32, 42 connected pixel extraction unit, 33 feature amount calculation unit, 34 attribute determination unit, 35 non-pattern region processing unit, 36 background region coating Crushing part, 37 design candidate area creating part, 38 expansion / contraction part, 43 basic rectangle defining part, 44 first separator detecting part, 45 line rectangular defining part, 46 second separator detecting part, 47 character area defining part, 48 noise determination Part, 49 character part specifying part.

Claims (5)

An image processing apparatus that determines a representative color of a target image area based on a pixel value in the target image area defined in the image data to be processed,
Means for determining a representative color candidate value from the image area of interest;
Correction means for correcting the luminance of the determined representative color candidate value and determining a representative color;
Including
The correction means includes
Regarding the luminance component of the representative color candidate value,
The output value for the input value from the minimum value MIN to the first threshold value TH1 is the minimum value MIN, and the output value for the second threshold value TH2 (where TH2> TH1) to the maximum value MAX is the maximum value. Correct based on a correction function set to be MAX,
The information processing apparatus according to claim 1, wherein the determined representative color information is subjected to a predetermined process on the image data to be processed. The image processing apparatus according to claim 1 .
The correction function further includes:
An image processing apparatus, wherein when an input value is a central value MID between a maximum value and a minimum value, an output value corresponding to the value is set to MID. The image processing apparatus according to claim 1.
When the color difference component of the representative color candidate value satisfies a predetermined condition, the correction unit performs correction to reduce the number of gradations related to the luminance component value of the representative color candidate value, and obtains the corrected value. An image processing apparatus characterized by being determined as a representative value. The image processing apparatus according to claim 3.
The predetermined condition is that the color difference components a * and b * of the representative value candidates expressed in the color space of L * a * b are within a predetermined range from the center value of the corresponding color difference component value range. An image processing apparatus characterized by the above. An image processing program for causing a computer to determine a representative color of a target image area based on a pixel value in the target image area defined in the image data to be processed,
Computer
Means for determining a representative color candidate value from the image area of interest;
Correction means for correcting the luminance of the determined representative color candidate value and determining a representative color;
Function as
In the correction means, the computer
Regarding the luminance component of the representative color candidate value,
The output value for the input value from the minimum value MIN to the first threshold value TH1 is the minimum value MIN, and the output value for the second threshold value TH2 (where TH2> TH1) to the maximum value MAX is the maximum value. Correction based on a correction function set to be MAX,
An image processing program characterized in that the determined representative color information is subjected to a predetermined process for the image data to be processed.

Images