Abstract:
An image processing device includes: a separating unit configured to separate colors of a plurality of pixels included in an input color image into a plurality of color groups on the basis of similarities between the colors of the pixels; and a conversion unit configured to generate a monochrome image by performing correction on each of the pixels of the color image on the basis of a grayscale representation assigned to each of plurality of the color groups.

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is based upon and claims the benefit of priority of the prior Japanese Patent Application No. 2011-61010, filed on Mar. 18, 2011, the entire contents of which are incorporated herein by reference. 
     FIELD 
     The embodiments discussed herein are related to an image processing device, an image processing method, and a storage medium for storing an image processing program. 
     BACKGROUND 
     In general, in order to convert a color image into a monochrome image, the brightness of each of the pixels of the monochrome image is determined on the basis of each of the pixels of the color image. For example, according to a technique described in Japanese Laid-open Patent Publication No. 2001-16459, RGB signals in an RGB color space are converted into LHC signals in an LHC space. The converted LHC signals are subjected to color tuning and are re-converted into RGB signals. Thereafter, each of the RGB signals is converted into a monochrome signal Y using the conversion equation “Y=0.3R+0.6G+0.1B” and is output. 
     SUMMARY 
     According to an aspect of the invention, an image processing device includes: a separating unit configured to separate colors of a plurality of pixels included in an input color image into a plurality of color groups on the basis of similarities between the colors of the pixels; and a conversion unit configured to generate a monochrome image by performing correction on each of the pixels of the color image on the basis of a grayscale representation assigned to each of the plurality of the color groups. 
     The object and advantages of the invention will be realized and attained by means of the elements and combinations particularly pointed out in the claims. 
     It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory and are not restrictive of the invention, as claimed. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a functional block diagram of an image processing device according to an embodiment; 
         FIG. 2  is a block diagram of a computer serving as the image processing device; 
         FIG. 3  is a flowchart of a color group separating and representative color computing process; 
         FIGS. 4A and 4B  are schematic illustrations of an example of a result of a group dividing process; 
         FIG. 5  is a flowchart of a conversion process according to a first embodiment; 
         FIG. 6  is a schematic illustration of an example of the flow of the conversion process according to the first embodiment; 
         FIG. 7  illustrates an example of the density values assigned to color groups; 
         FIG. 8  is a flowchart of a conversion process according to a second embodiment; 
         FIGS. 9A to 9D  illustrate examples of the image of a screen pattern; 
         FIGS. 10A to 10F  illustrate examples of the image of a screen pattern; and 
         FIG. 11  illustrates an example of data stored in a pixel list. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     When the brightness of each of the pixels of a monochrome image is determined using the brightness of a corresponding pixel of a color image, pixels of the color image having the same brightness may be converted into pixels of the monochrome image having the same brightness even when the colors of the pixels of the color image differs from one another. For example, let L denote the brightness of a pixel of a monochrome image. Then, L is computed as the average brightness of three colors R, G, and B of the pixel in a color image using an RGB color space. Accordingly, the average brightness is computed as follows:
 
 L =( R+G+B )/3.
 
     In such a case, the brightness values L of the pixels of the monochrome image become the same even when the pixels of the color image have different colors. For example, in the case of a red pixel (R=255, G=0, B=0), the brightness L=(255+0+0)/3=85. In the case of a green pixel (R=0, G=255, B=0), the brightness L=(0+255+0)/3=85. In the case of a blue pixel (R=0, G=0, B=255), the brightness L=(0+0+255)/3=85. 
     In addition, when the above-described equation “Y=0.3R+0.6G+0.1B” or other conversion equations are used, pixels having the same brightness defined by the conversion equation in a color image have the same brightness in the monochrome image even when the colors of the pixels in the color image differ from one another. Therefore, a difference in color in a color image before conversion is not perceivable in the monochrome image after conversion. Thus, the visibility of the monochrome image disadvantageously decreases. 
     Accordingly, the present technology provides an image processing device, an image processing method, and a storage medium for storing an image processing program that convert a color image into a monochrome image that allows a difference in color in the color image to be perceivable. 
     Embodiments of the present technology are described in detail below with reference to the accompanying drawings. Note that the embodiments below are mainly described with reference to an image process performed on a color image including a natural image region. However, the image process according to the embodiments is applicable to a color image that does not include a natural image region. In addition, in the embodiments described below, the term “color value” or “density” is also referred to as “brightness”. In addition, the embodiments may be combined and performed if the consistency of the combination is preserved. 
     First Embodiment 
       FIG. 1  is a functional block diagram of an image processing device  10  according to a first embodiment. The image processing device  10  converts a color image into a monochrome image. Note that the term “monochrome image” refers to an image that represents a difference in gray scale using a difference in brightness of a single color. The image processing device  10  includes an acquiring unit  12 , an extracting unit  14 , a separating unit  16 , a computing unit  18 , a conversion unit  20 , a monochromatizing unit  22 , a combining unit  24 , and an output unit  26 . 
     The image processing device  10  may be achieved by using, for example, a computer  30  illustrated in  FIG. 2 . The computer  30  includes a central processing unit (CPU)  32 , a memory  34 , and a nonvolatile storage unit  36 , which are connected to one another via a bus  38 . Note that examples of the memory  34  include a random access memory (RAM) and a read only memory (ROM). The storage unit  36  may be formed from, for example, a hard disk drive (HDD) or a flash memory. 
     In addition, the computer  30  has an input unit (not illustrated) connected thereto via the bus  38 . When a user operates the input unit, the input unit sends information in accordance with the type of operation to the CPU  32 . Examples of the input unit include a keyboard and a mouse. In addition, the computer  30  has an output unit connected thereto via the bus  38 . The output unit outputs a result of processing performed by the computer  30 . Examples of the output unit include a display unit and a printing unit. Furthermore, the computer  30  has a network interface (not illustrated) connected thereto via the bus  38 . The network interface manages data exchanged with another computer wired or wirelessly. Still furthermore, the computer  30  may have a media drive unit (not illustrated) connected thereto via the bus  38 . The media drive unit reads and writes data from and to a removable recording medium. 
     The storage unit  36  serving as a recording medium stores an image processing program  40 . The image processing program  40  causes the computer  30  to function as the image processing device  10 . The storage unit  36  has an image data storage area  58  for storing the image data of a color image to be processed by the image processing device  10 . The CPU  32  reads the image processing program  40  out of the storage unit  36  and loads the image processing program  40  into the memory  34 . Thereafter, the CPU  32  sequentially executes the processes of the image processing program  40 . 
     The image processing program  40  includes an image acquiring process  42 , a natural image extracting process  44 , a color group separating process  46 , a representative color computing process  48 , a conversion process  50 , a natural image monochromatizing process  52 , an image combining process  54 , and an image output process  56 . The CPU  32  functions as the acquiring unit  12  illustrated in  FIG. 1  by performing the image acquiring process  42 . In addition, the CPU  32  functions as the extracting unit  14  illustrated in  FIG. 1  by performing the natural image extracting process  44 . The CPU  32  functions as the separating unit  16  illustrated in  FIG. 1  by performing the color group separating process  46 . The CPU  32  functions as the computing unit  18  illustrated in  FIG. 1  by performing the representative color computing process  48 . Furthermore, the CPU  32  functions as the conversion unit  20  illustrated in  FIG. 1  by performing the conversion process  50 . The CPU  32  functions as the monochromatizing unit  22  illustrated in  FIG. 1  by performing the natural image monochromatizing process  52 . Still furthermore, the CPU  32  functions as the combining unit  24  illustrated in  FIG. 1  by performing the image combining process  54 . Yet still furthermore, the CPU  32  functions as the output unit  26  illustrated in  FIG. 1  by performing the image output process  56 . 
     When the image processing device  10  is realized by using the computer  30 , the computer  30  that executes the image processing program  40  functions as the image processing device  10 . While the present embodiment has been described with reference to the image processing program  40  read from the storage unit  36 , the image processing program  40  may be read from any type of storage medium, such as a CD-ROM or a DVD-ROM, and be executed. The storage medium to store the image processing program does not include a transitory medium such as a propagation signal. In addition, the image processing device  10  may be formed from, for example, a semiconductor integrated circuit and, more particularly, an application specific integrated circuit (ASIC). In this case, the functional units of the image processing device  10  may be realized using, for example, electronic circuits. 
     The acquiring unit  12  acquires the image data of a color image to be processed by the image processing device  10 . For example, the acquiring unit  12  acquires the image data by reading the image data of the color image to be processed from the image data storage area  58  of the storage unit  36 . Alternatively, the acquiring unit  12  may be a document reading unit, such as a scanner, disposed outside the image processing device  10  or a communication unit that acquires the image data by communicating with an external image processing device having a storage unit storing image data. Still alternatively, the acquiring unit  12  may be formed from an application interface that receives data from an application that generates an image. Note that the acquiring unit  12  formed from a communication unit is used when, for example, the computer  30  serving as the image processing device  10  is connected to the above-described external document reading unit or image processing device via a local area network (LAN). 
     Note that examples of a color image to be monochromatized according to the present embodiment include a color image generated by an application program running on the computer  30  or a different computer (e.g., an illustration or a graph) and a text image using a plurality of colors for the characters. Thus, according to the present embodiment, the image processing device  10  processes a human-made color image or an image partially including a human-made color image. Note that an image to be processed may be an image having a natural image region (e.g., a photo image region) disposed outside a human-made color image region. A typical example of such an image is an image obtained by scanning a document generated by combining characters and images. The acquiring unit  12  acquires the image data of such an image as image data to be processed. 
     In addition, the color space of the image data of the color image acquired by the acquiring unit  12  may be any one of the following widely used color spaces: an RGB color space, a CMYK color space, an L*a*b* color space, an XYZ color space. In the following description, as an example, the image data in an RGB color space is acquired by the acquiring unit  12 . 
     The extracting unit  14  separates the color image to be processed and represented by the image data acquired by the acquiring unit  12  into a natural image region and a region other than the natural image. More specifically, the color image to be processed is separated into a plurality of unit images first. Subsequently, the color distribution of the colors of the pixels included in each of the unit areas is obtained. Thereafter, the extracting unit  14  computes an evaluation value for evaluating the degree of non-uniformity of the color distribution for each of the unit regions. Note that, for example, the size of a distribution range obtained when the colors of the pixels in the unit region are plotted on a color coordinates may be used as the evaluation value. That is, for example, if the color coordinates are two-dimensional, the area of the distribution range may be used. Alternatively, if the color coordinates are three-dimensional, the volume of the distribution range may be used. However, any other evaluation value may be used. 
     Subsequently, the evaluation value computed for each of the unit areas is compared with a reference value. In this way, it is determined that each of the unit areas is the region of a natural image or the region of an image other than a natural image using the result of comparison. In general, a natural image includes pixels of various colors. That is, the non-uniformity of the distribution of each of the colors is small. Accordingly, if the evaluation value indicates a small non-uniformity of the color distribution (e.g., if an evaluation value indicating the above-described size of the distribution range is greater than or equal to a reference value), it may be determined that the target unit region is a region corresponding to a natural image. However, if the evaluation value indicates a large non-uniformity of the color distribution (e.g., if an evaluation value indicating the above-described size of the distribution range is less than the reference value), it may be determined that the target unit region is a region other than a natural image region, that is, a human-made image region. Thereafter, neighboring unit regions both corresponding to natural images are combined into one region. In addition, neighboring unit regions both corresponding to images other than a natural image are combined into one region. In this way, the color image to be processed is separated into a natural image region and a non-natural image region. If each of the unit areas of the color image to be processed has information indicating whether the region is a photo (i.e., a natural image) or a human-made image as attribute information, the color image may be separated into a natural image region and a non-natural image region by referring to the attribute information. Note that the extracting unit  14  serves as an example of an extracting unit according to the present technology. 
     The extracting unit  14  outputs color image data corresponding to a natural image region of the color image to be processed to the monochromatizing unit  22 . The monochromatizing unit  22  converts data indicating the color of each of the pixels among color image data corresponding to the natural image region input from the extracting unit  14  into data indicating the density of the pixel. That is, the monochromatizing unit  22  converts the color image data of the natural image region into monochrome image data. For example, in order to convert the color image data into the monochrome image data, the monochromatizing unit  22  computes a color-value component of each of the pixels of the unconverted color image data. Thereafter, the density of the pixel in a monochrome image is determined by using the computed color-value component. At that time, one of widely used processing techniques may be applied. 
     More specifically, for example, the color space of the color image data may be converted from an RGB color space into an L*a*b* color space and, thereafter, a process for computing the density value of each of the pixels of monochrome image data from a color value L* of the pixel subjected to the conversion may be applied. Alternatively, for example, an average value of the R, G, and B values (i.e., (R+G+B)/3) may be computed for each of the pixels and, thereafter, the computed value may be used as the density value of the pixel in the monochrome image data. Still alternatively, the R, G, B values may be multiplied by different coefficients and be summed (i.e., r·R+g·G+b·B where r, g, and b are coefficients) for each of the pixels. The computed value may be used as the density value of the pixel of monochrome image data. Yet still alternatively, the weighted average of the R, G, and B values may be used. The monochromatizing unit  22  outputs, to the combining unit  24 , the monochrome image data of the natural image region obtained through the above-described process. 
     In addition, the extracting unit  14  outputs, to the separating unit  16 , the color image data of the image region other than the natural image region of the color image to be processed. The separating unit  16  separates the color distribution of the pixels of the non-natural image region input from the extracting unit  14  into a plurality of color groups (described in more detail below). The computing unit  18  computes a representative color for each of the separated color groups. The conversion unit  20  determines the density assigned to each of the color groups on the basis of the representative color computed for the color group. Thereafter, the conversion unit  20  makes the density of each of the pixels of the non-natural image region the same as the density assigned to the color group that includes the pixel. This operation corresponds to a conversion process described below. Thereafter, the conversion unit  20  outputs, to the combining unit  24 , the monochrome image data of the non-natural image region obtained through the above-described process. 
     The combining unit  24  combines the monochrome image data of the natural image region input from the monochromatizing unit  22  with the monochrome image data of the non-natural image region input from the conversion unit  20  into the image data of a single monochrome image. Thereafter, the combining unit  24  outputs the combined monochrome image data to the output unit  26 . 
     The output unit  26  outputs a monochrome image indicated by the image data input from the combining unit  24  so that the image is viewable by the user. An example of such a process is a process in which the image data is output to a printing apparatus that prints an image on a sheet of paper and the printing apparatus prints, on a sheet of paper, a monochrome image indicated by the input image data. If the image processing device  10  is included in a printing apparatus, another example of such a process is a process in which the output unit  26  instructs a printing unit of the printing apparatus to print the monochrome image. The printing apparatus may be a widely used type of printing apparatus, such an electrophotographic printing apparatus, an inkjet printing apparatus, or a press plate printing apparatus. Alternatively, the image data may be output to a display apparatus that displays an image on a screen, and a monochrome image represented by the input image data may be displayed on the screen of the display apparatus. 
     The operation of the first embodiment is described next. In existing techniques, in order to monochromatize a color image, as in the processing performed by the monochromatizing unit  22 , the color-value component of each of the pixels is computed from the color of the pixel of the unconverted image, and a process for determining the density of the pixel of the monochrome image from the computed color-value component is performed. In a natural image, the colors of neighboring pixels are rarely the same. In general, the colors of the pixels differ from each other. Accordingly, in a general monochromatizing process for a natural image, even when some pixels having different colors in the original color image are reproduced as pixels having the same density in the converted monochrome image, the impact on the image quality of the monochrome image is small. Thus, as a whole, the reproducibility of the original color image is high. 
     In contrast, in a human-made color image (e.g., a color image of an illustration or a graph or a text image using a plurality of colors for characters), areas each having a certain color (i.e., a region in which pixels of the same color are continuously arranged) are scattered throughout the image. That is, a human-made color image has a non-uniform color distribution. If an existing monochromatizing process is applied to such an image, portions of the original color image having different colors may be reproduced as portions of a converted monochrome image having the same density. That is, such phenomenon occurs for each of the areas of the original color image having a certain color. Thus, if two areas that have different colors in the original color image and are reproduced as areas having the same density in the monochrome image converted from the original color image neighbor each other, it is difficult to distinguish between the two areas of the converted monochrome image as the areas having different colors in the original color image. 
     For example, assume that normal characters in text are colored using a first color, characters of a specific portion of the text are colored using a second color, and an image including the text image is monochromatized. In this case, if the brightness (the color value) of the first color significantly differs from that of the second color, the characters of the first color are reproduced as characters having a different density from that of the characters of the first color in the converted monochrome image even when an existing monochromatizing process is applied to the text image. However, when an existing monochromatizing process is applied to the text image and if the brightness of the first color is the same as or close to the second color, the characters of the first color and the characters of the second color in the original text image are reproduced with the same density or close densities in the converted monochrome image. Accordingly, in the converted monochrome image, it is significantly difficult to distinguish the characters of the first color in the original text image from the characters of the second color in the original text image. 
     In addition, for example, assume that a first region of a graph is colored with a first color, a second region different from the first region is colored with a second color different from the first color, and an image including the graph is monochromatized. In this case, like the above-described colors in text, if an existing monochromatizing process is applied, the first color and the second color are represented as the same density or close densities in the monochrome image. For example, it is difficult to distinguish neighboring first and second regions of a bar graph or a circle graph from each other. While the above description has been made with reference to a bar graph or a circle graph, the type of graph is not limited thereto. For example, even when a graph having line portions of different colors, such as a line graph, is used, the same problem arises. 
     Therefore, according to the present embodiment, in a monochromatizing process, an image region of a color image that has a non-uniform color distribution is monochromatized using the separating unit  16 , the computing unit  18 , and the conversion unit  20  as follows. 
     A color group separating and representative color computing process performed by the separating unit  16  and the computing unit  18  is described first with reference to  FIG. 3 . As described above, the extracting unit  14  outputs, to the separating unit  16 , the color image data of a non-natural image region of a color image to be processed. Accordingly, the color image data input to the separating unit  16  by the extracting unit  14  is the color image data of an image region other than a natural image region. In the color group separating and representative color computing process illustrated in  FIG. 3 , the separating unit  16  clears the storage area of a pixel list (described in more detail below) in the storage area of the memory  34 . Thus, an initialization process in which the storage area of the pixel list having m records in the memory  34  is set to 0 is performed (process  70 ). Subsequently, the separating unit  16  attempts to read the data of a pixel to be processed from the color image data input from the extracting unit  14  (process  72 ). Thereafter, the separating unit  16  determines whether all of the pixels of the color image data have been processed (process  74 ). If all of the pixels of the color image data have already been read and, therefore, the extracting unit  14  fails to read a new pixel in process  72 , the determination is “Yes”. Thereafter, if, in process  74 , the determination is “Yes”, the color group separating and representative color computing process is completed. 
     However, if, in process  72 , the data of a new pixel to be processed may be read, the determination made in process  74  is “No”. Thereafter, the separating unit  16  determines whether the information regarding a pixel having a color within a color difference range in which the color may be regarded as the same as the color of the currently processed pixel has been registered (process  76 ). In this embodiment, the color difference range in which the color may be regarded as the same as the color of the currently processed pixel is set in advance or is set by the user in the form of a parameter used when the process is performed. For example, a threshold value indicating the distance between the pixels in the color space or the sum of absolute values between the pixel value components is set, and if the color difference is less than or equal to the threshold distance or the threshold sum, the two pixel values may be regarded as the same value. 
     Subsequently, the separating unit  16  determines whether the information regarding a pixel having a color within a color difference range in which the color may be regarded as the same as the color of the currently processed pixel may be extracted in process  76  (process  78 ). Note that when the image region is processed and if the data of a first pixel in the image region is read as a pixel to be processed, no record is present in the pixel list. That is, the determination made in process  78  is “No”. If the determination in process  78  is “No”, the separating unit  16  determines whether the number of the records in the pixel list stored in the memory  34  reaches a certain upper limit (process  80 ). 
     When the data of the first pixel is read as data to be processed, the number m of the records in the pixel list is 0 and, therefore, the determination made in process  80  is “No”. If the determination made in process  80  is “No”, the separating unit  16  generates a new record for the currently processed pixel that is to be registered (process  84 ). 
     An example of the data stored in the pixel list is illustrated in  FIG. 11 . The pixel list  200  includes a record  201  having fields in which information items “list number”, “representative color”, “number of pixels”, “color difference”, and “color information” are registered. The field “list number” contains the sequence number of the record in the pixel list. The field “representative color” contains the pixel value indicating, for example, the average color of all of the pixels registered in the record. The field “number of pixels” contains the number of pixels registered in the record. For example, in the record  201 , two pixels “Pixel  1 ” and “Pixel  2 ” are registered. Accordingly, the field “number of pixels” contains “2”. 
     The term “color difference” refers to information indicating a color difference between the pixel value of one of the pixels recorded in the record and the pixel value indicated by the information “representative color”. For example, in the record  201 , a color difference “C 1 ” between the pixel value of Pixel  1  and the representative color and a color difference “C 2 ” between the pixel value of Pixel  2  and the representative color are registered. The term “color information” refers to the pixel value of a pixel registered in the record. For example, in the record  201 , the pixel value “R 1 , G 1 , B 1 ” of Pixel  1  and the pixel value “R 2 , G 2 , B 2 ” of Pixel  2  are registered. 
     When the separating unit  16  generates a new record in the pixel list, the new record has “number of pixels” set to 1, “representative color” and “color information” each set to the color information regarding of the currently processed pixel. Thereafter, the separating unit  16  increments the number m of the records stored in the memory  34  by one (process  86 ). After the process  86  has been completed, the processing returns to process  72 , where the separating unit  16  reads the data of a new pixel as the data of a pixel to be processed. Subsequently, the above-described processing is repeated. 
     However, if the currently processed pixel has a color that is the same as the color of the previously processed pixel in the color group separating process, the information regarding the pixel having the same color as that of the currently processed pixel is extracted in process  76  (“Yes” in process  78 ). In such a case, the separating unit  16  and the computing unit  18  additionally registers the information regarding the currently processed pixel in the record of the pixel list in which the information regarding the pixel having the same color extracted in process  76  (process  82 ) has been registered. 
     More specifically, the separating unit  16  increments “number of pixels” in the record by one and additionally registers the color information regarding the currently processed pixel in the field “color information”. In addition, using the color information regarding a plurality of pixels registered in the “color information” field of the record, the computing unit  18  computes a new representative color and updates the “representative color” into the new computed representative color. Furthermore, the computing unit  18  computes the color difference between the new representative color and the color of each of the pixels registered in the “color information” field. Thereafter, the “color difference” in the record is updated into the computed color differences. 
     Note that for example, as the representative color, the average color for each of the color components R, G, and B of all of the pixels registered in a record may be employed. Alternatively, a color computed using another computing method may be used (e.g., the color corresponding to the centroid point of the distribution range in the color coordinates of all of the pixels in the record). In addition, for example, as the color difference between the representative color and the color of each of the pixels, a color difference ΔC (a difference between the representative color and the color of each of the pixels in the color coordinates) computed by using the following equation (1) may be used:
 
Δ C =√(( R   i   =R   0 )) 2 +( G   i   −G   0 ) 2 +( B   i   −B   0 ) 2 )  (1)
 
     where R i , G i , B i  denote the values of the color components of each of the pixels, and R 0 , G 0 , B 0  denote the values of the color components of the representative color. Still alternatively, a color computed using another computing method may be used. After the above-described process  82  has been completed, the processing returns to process  72 , where the separating unit  16  reads the data of a new pixel as the data of a pixel to be processed. Thereafter, the above-described processing is repeated. 
     The data is sequentially read through the above-described processing until the number m of the records in the pixel list reaches the upper limit. Thus, among the pixels to be processed, the pixels having the same color are registered in the same record. However, the pixels having different colors are registered in different records. If the number m of the records reaches the upper limit, the determination made in operation  80  is “Yes” and, thus, the processing proceeds to process  88 . 
     In such a case, the separating unit  16  searches a set of the pixels that has been processed before the current time and the pixels registered in the pixel list for a pair of pixels registered in different records and having a minimum color difference (process  88 ). That is, the plurality of pixels that have been processed before the current time include the pixel that is currently processed and the pixels having the information registered in the pixel list. If a pair of pixels that satisfies the condition is extracted, the separating unit  16  and the computing unit  18  register, in the record for one of the two pixels having the information registered in the record, the information regarding the other pixel (process  90 ). 
     Note that if one of the two pixels is the currently processed pixel read in process  72 , the information regarding the currently processed pixel is additionally registered in the record of the pixel list including the information of the other pixel in process  90  as in the above-described process  82 . 
     If the two pixels have already been registered in the pixel list, the information regarding one of the pixels is moved into the record of the pixel list including the information of the other pixel in process  90 . In this case, the information regarding either one of the pixels may be moved. However, it is desirable that the information of the pixel registered in the record having the smaller value in the field “number of pixels” be moved. This is because the number of loops from process  88  to process  94  is reduced and, therefore, the processing time is highly likely reduced. 
     In order to move the information regarding the pixel that has already been registered in the pixel list, the separating unit  16  performs the above-described additional registration process described in process  82 . In addition, the separating unit  16  deletes the information regarding the moved pixel from the field “color information” of the record of the pixel list and updates the “number of pixels”. Furthermore, the computing unit  18  updates the “representative color” and deletes the information in the “color difference” field of the record of the pixel list including the information regarding the moved pixel. 
     Subsequently, the separating unit  16  determines whether the information regarding the pixel that is read in operation  72  and that is currently processed has been registered in any one of the records of the pixel list (process  92 ). If the determination is “No”, the separating unit  16  determines whether a record having a “number of pixels” of 0, that is, an empty record appears in the pixel list (process  94 ). If the determination is “No”, the processing returns to process  88 . Thereafter, processes  88  to  94  are repeated until the information regarding the currently processed pixel is registered in any one of the records of the pixel list or until the record for registering the information regarding the currently processed pixel may be generated in the pixel list. 
     If the information regarding the currently processed pixel is registered in any one of the records of the pixel list, the determination made in process  92  is “No” and, therefore, the processing returns to process  72 . However, if an empty record appears, the determination made in process  94  is “Yes” and, therefore, the separating unit  16  generates a new record in which the currently processed pixel is registered in the pixel list (process  96 ). Thereafter, the processing returns to process  72 . 
     The above-described processing is repeated until the determination made in process  74  becomes “Yes”. Accordingly, when, for example, the upper limit of the number m of the records in the pixel list is 2, two records or one record is generated. The information regarding each of the pixels is registered in one of the two records or one record. In this way, the color distribution of the pixels in the image region indicated by the image data input from the extracting unit  14  is separated into two color groups having the information registered in the different records of the pixel list, as illustrated an image in  FIG. 4A . In the image illustrated in  FIG. 4A , the abscissa indicates the R value of a pixel while the ordinate indicates the B value of the pixel. Alternatively, when, for example, the upper limit of the number m of the records in the pixel list is 4, a maximum of four records are generated. The information regarding each of the pixels is registered in one of the maximum of four records. In this way, the color distribution of the pixels in the image region indicated by the color image data input from the extracting unit  14  is separated into four color groups having the information registered in the different records of the pixel list, as illustrated in  FIG. 4B . In the image illustrated in  FIG. 4B , the abscissa indicates the R value of a pixel while the ordinate indicates the B value of the pixel. 
     Note that each of the color groups includes at least one pixel. Let at least one pixel form a pixel group corresponding to a color group. Then, a pixel group included in a color group may be scattered in the screen data, may be lumped and located at a plurality of sub-areas, or may be lumped and located inside of one sub-area. The location of a pixel group corresponding to a color group in the screen data is determined by, for example, the XY coordinates of each of the pixels in the screen data. 
     The conversion process performed by the conversion unit  20  is described in detail next with reference to  FIG. 5 . Note that as described above, the conversion unit  20  determines the density to be assigned to each of the color groups on the basis of the representative color of the color group computed by the computing unit  18 . Thereafter, the conversion unit  20  makes the density of each of the pixels in a non-natural image region the same as the density assigned to the color group including the pixel. 
     In the conversion process illustrated in  FIG. 5 , the conversion unit  20  sequentially reads the representative color information regarding each of the color groups from each of the records of the pixel list first (process  100 ). Subsequently, the conversion unit  20  computes the density for the representative color of each of the color groups on the basis of the representative color information read in process  100  (process  102 ). 
     Note that according to the present embodiment, the densities for the representative colors are used for ranking the densities of the color groups. Accordingly, a density of the representative color that is roughly computed is sufficient.  FIG. 6  is a schematic illustration of an example of the flow of the conversion process according to the first embodiment. As illustrated in  FIG. 6 , the sum of some of the R, G, and B values of the representative color (e.g., the sum of the R and B values) may be used. In the example illustrated in  FIG. 6 , for a color group  1 , the representative color is determined by R 0 =2 and B 0 =70. The sum of the values (=72) is used as the density of the representative color. For a color group  2 , the representative color is determined by R 0 =50 and B 0 =52. The sum of the values (=102) is used as the density of the representative color. In addition, for a color group  3 , the representative color is determined by R 0 =245 and B 0 =294. The sum of the values (=494) is used as the density of the representative color. For a color group  4 , the representative color is determined by R 0 =202 and B 0 =3. The sum of the values (=205) is used as the density of the representative color. However, the sum of the R, G, and B values of the representative color may be used. Alternatively, all or some of the R, G, and B values may be multiplied by corresponding to certain coefficients, and the sum of the products may be used. 
     Subsequently, the conversion unit  20  ranks the densities of the representative colors of the color groups computed in process  102  on the basis of a greater-lesser relationship of the densities of the representative colors (process  104 ). For example, in the example illustrated in  FIG. 6 , the densities of the representative colors of the color groups are ranked in the ascending order of the densities of the representative colors of the color groups. The color group  1  having the lowest density (=72) of the representative color is ranked first. The color group  2  having the second lowest density (=102) of the representative color is ranked second. The color group  4  having the second highest density (=205) of the representative color is ranked third. The color group  3  having the highest density (=494) of the representative color is ranked fourth. 
     Subsequently, the conversion unit  20  determines the densities to be assigned to the color groups in the monochrome image on the basis of the ranks of the densities of the representative colors of the color groups obtained through the process  104  (process  106 ). According to the first embodiment, the density assigned to each of the color groups is determined so that the dynamic range of the density (i.e., the difference between the highest value and the lowest value of the density) of the converted monochrome image is larger than the dynamic range of the unconverted color image. 
     More specifically, the conversion unit  20  separates a numerical range between the lowest value (=0) and the highest value (=2 n −1) of a theoretical density, which are determined by the number of bits of the data indicating the density, into a plurality of numerical ranges in accordance with the number m of the records. Note that the numerical ranges are determined so that the difference between the widths of two numerical ranges is minimized. In the first embodiment, a monochrome image to be printed on a sheet of paper is obtained. Accordingly, the lowest value of the density (=0) is assigned to the base color of paper (white). Thus, the conversion unit  20  separates the numerical range between the lowest value and the highest value of the theoretical density into m numerical ranges, which is the number that is the same as the number of the color groups m. Thereafter, the conversion unit  20  extracts m density values corresponding to the borders between the separated numerical ranges and assigns each of the m extracted density values to one of the color groups in accordance with the ranks of densities of the representative colors of the color groups.  FIG. 7  illustrates m density values corresponding to the borders between the separated numerical ranges. In  FIG. 7 , the ordinate represents the density. The symbol “O” on the right side of  FIG. 7  indicates the determined density value of the representative color of each of the color groups. As illustrated in  FIG. 7 , a difference between the density values determined in process  106  and indicated by the symbols “O” on the right side of  FIG. 7  is larger than a difference between the density values of the representative colors of the color groups on the left side of  FIG. 7 . As described above, the density values assigned to the color groups are determined so that the dynamic range of the density of the converted monochrome image is wider than the dynamic range of the density of the unconverted color image. 
     A specific example of determining the density assigned to each of the color group is described next. For example, if the number of bits of data indicating density is 8, the highest theoretical density is 2 8 −1 (=255). For example, when the number of the color groups is 4 and if the lowest value of the density (=0) is assigned to the base color of paper (white), the range of the density between the lowest value and the highest value is separated into 4 numerical ranges (also refer to  FIG. 7 ). Thus, as illustrated in  FIG. 6 , for example, the values “66”, “129”, “192”, and “255” assigned to the color groups are obtained. Note that in this example, the range of the density between the lowest value and the highest value is separated into 4 numerical ranges so that the widths of the separated numerical ranges (the differences between the density values assigned to the color groups) are substantially the same. By separating the range of the density so that the differences between the density values are substantially the same, the different color groups may be easily distinguished from one another in an image output as a result of the monochromatizing process. 
     In the example illustrated in  FIG. 6 , the lowest density value “66” is assigned to the color group  1  that is ranked first in the order of the density of the representative color of a color group (in the ascending order). In addition, the second lowest density value “129” is assigned to the color group  2  that is ranked second in the order of the density of the representative color of a color group (in the ascending order). Furthermore, the third lowest density value “192” is assigned to the color group  4  that is ranked third in the order of the density of the representative color of a color group (in the ascending order). Still furthermore, the highest density value “255” is assigned to the color group  3  that is ranked fourth in the order of the density of the representative color of a color group (in the ascending order). 
     Subsequently, the conversion unit  20  converts the color image data of the non-natural image region output from the extracting unit  14  into monochrome image data. That is, the conversion unit  20  sets a variable i to 1 (process  108 ). Thereafter, the conversion unit  20  converts the color information regarding each of the pixels of the color image data to be converted and included in a color group i into the density information indicating the density assigned to the color group i in process  106  (process  110 ). Subsequently, the conversion unit  20  determines whether the variable i reaches the number m of the records in the pixel list (i.e., the number of color groups) (process  112 ). If the determination is “No”, the conversion unit  20  increments the variable i by one (process  114 ). 
     After the process  114  is performed, the processing returns to process  110 . Thereafter, processes  110  to  114  are repeated until the determination made in process  112  becomes “Yes”. If the determination made in process  112  becomes “Yes”, the conversion process is completed. In this way, the color image in the non-natural image region is converted into a monochrome image in which the densities of the pixels in different color groups are different and the dynamic range of the density is increased. 
     Note that the brightness assigned to each of the color groups may be determined without computing the brightness of the representative color of each of the color groups and without taking into account the greater-lesser brightness relationship among the representative colors. For example, the brightness assigned to each of the color groups may be determined in accordance with the number of the color groups without using the rank of the brightness of the color group. In such a case, processes  102  and  104  are removed. If processes  102  and  104  are removed, process  106  may be performed immediately after process  100 . In this case, in process  106 , the brightness of each of the color groups may be determined on the basis of the order of the list number of the pixel list. 
     As described above, according to the first embodiment, for the color image data of a non-natural image region (i.e., the color image data having a non-uniform color distribution), the color distribution in the image region is separated into a plurality of color groups. Thereafter, different densities are assigned to the color groups in order to represent different grayscales. In this way, the areas of the original color image having different colors are reproduced as the areas of the converted monochrome image having different densities. Thus, the areas of the converted monochrome image may be easily distinguished from one another as the areas of the original color image having different colors. 
     For example, when a text image including characters of a first color and characters of a second color is monochromatized and if the hue of the first color differs from the hue of the second color and the color values of the first and second colors are similar to each other, the characters of the first color and the characters of the second color in the original text image are reproduced in a monochrome image using different densities. Accordingly, the areas of the original color image having different colors may be easily distinguished in the converted color image data. 
     In addition, according to the first embodiment, the brightness assigned to each of the color groups in a monochromatized image is determined in accordance with the brightness of each of the color groups in the color image. In this way, the visible grayscale of the monochromatized image may be made similar to the visible grayscale of the color image. Thus, visual discomfort that a user feels when the user looks at a monochrome image converted from a color image may be reduced. Furthermore, according to the first embodiment, during separation of the color distribution, the brightness assigned to each of the color groups is determined so that the differences between the brightness values are substantially the same. In this way, the color groups having different colors may be easily distinguished from one another in an image output as a result of the monochromatizing process. 
     Second Embodiment 
     A second embodiment of the present technology is described next. Note that the second embodiment is similar to the above-described first embodiment except for the conversion process. Accordingly, the same numbering will be used in referring to the components of the second embodiment as is utilized above in describing the first embodiment, and the description of the configuration of the second embodiment is not repeated. The conversion process according to the second embodiment is described in detail below with reference to  FIG. 8 . 
     In the conversion process according to the second embodiment, the conversion unit  20  performs the processes that are the same as processes  100  to  104  of the conversion process of the first embodiment (refer to  FIG. 5 ). Thereafter, from among a plurality of screen patterns prestored in the storage unit  36 , the conversion unit  20  selects a screen pattern to be assigned to each of the color groups in a monochrome image in accordance of the ranks of the densities of the representative colors of the color groups (process  120 ). 
     The screen pattern is selected so that the screen patterns assigned to the color groups are distinguished from one another in the monochrome image. For example, according to the present embodiment, halftone dots applicable to the screen pattern are based on a technique for representing the grayscale in a binary image by varying the area ratio for a unit region. In general, the area ratio or the number of the lines of the halftone dots, the shape of the pattern, and the angle of the pattern arrangement is selected in accordance with, for example, the output resolution or the output grayscale. According to the present embodiment, by varying at least one of the area ratio, the number of the lines of the halftone dots, the shape of the pattern, and the angle of the pattern arrangement, the screen patterns may be distinguished from one another in a monochrome image. 
       FIGS. 9A to 9D  illustrate an example of variations in the halftone dot screen pattern. If, as illustrated in  FIG. 9A , the area ratio of halftone dots in the halftone dot screen pattern is varied, the regions of the monochrome image having the screen pattern are distinguished from one another as regions having different grayscale representations. Alternatively, even when, as illustrated in  FIG. 9B , the number of lines of the halftone dot screen pattern is varied, the regions of the monochrome image having the screen pattern are distinguished from one other as regions having different grayscale representations. Still alternatively, even when, as illustrated in  FIG. 9C , the shape of the halftone dot screen pattern is varied, the regions of the monochrome image having the screen pattern are distinguished from one another as regions having different grayscale representations. Yet still alternatively, even when, as illustrated in  FIG. 9D , the angle of the halftone dot arrangement in a halftone dot screen pattern is varied, the regions of the monochrome image having the screen pattern are distinguished from one another as regions having different grayscale representations. 
     Accordingly, if the plurality of screen patterns stored in the storage unit  36  are halftone dot screen patterns, the conversion unit  20  selects one of the screen patterns to be assigned to each of the color groups in the monochrome image as follows. That is, the conversion unit  20  selects the screen patterns that have at least one of different halftone dot area ratios, different numbers of lines of halftone dots, different shapes of a pattern, and different angles of a pattern arrangement and that are recognized as patterns having different grayscales in the monochrome image. The number of the selected screen patterns is the same as the number of the color groups. Thereafter, the conversion unit  20  ranks the selected screen patterns using the level of grayscales represented by the screen patterns. The screen patterns are assigned to the color groups having the ranks of the densities of the representative colors that are the same as the ranks of the screen patterns. In this way, the color groups have the screen patterns assigned thereto in accordance with the ranks of the densities of the representative colors. 
     In addition, according to the second embodiment, the conversion unit  20  performs a process for converting a region corresponding to the pixels of a color group i into the region of the screen pattern assigned to the color group i (process  122 ) instead of the process for converting the color information regarding the pixels included in the color group i into the density information (process  110  illustrated in  FIG. 5 ). The above-described processing is performed on each of the color groups and, therefore, the regions of the original color image having different colors are reproduced in the converted monochrome image as regions having different screen patterns, that is, different grayscale representations. Thus, the regions of the monochrome image having different screen patterns are recognized as the regions of the original color image having different colors. 
     Note that a screen pattern to be assigned to each of the color groups may be determined without computing the density of the representative color of each of the color group and without taking into account a greater-lesser brightness relationship among the densities of the representative colors. For example, the screen patterns to be assigned to the color groups may be selected in accordance with the total number of the color groups. In such a case, processes  102  and  104  are removed. If processes  102  and  104  are removed, process  120  may be performed immediately after process  100 . In this case, in process  120 , the screen patterns corresponding to the color groups may be determined on the basis of the order of the list number of the pixel list. 
     As described above, according to the second embodiment, for the color image data of a non-natural image region (i.e., the color image data having a non-uniform color distribution), the color distribution in the image region is separated into a plurality of color groups. Thereafter, different screen patterns are assigned to the color groups in order to represent different grayscales. In this way, the areas of the original color image having different colors are reproduced as the areas of the converted monochrome image having the different screen patterns. Thus, the areas of the converted monochrome image may be easily distinguished from one another as the areas of the original color image having different colors. 
     In addition, according to the second embodiment, during the monochromatizing process, a screen pattern assigned to each of the color groups is determined in accordance with the density of the color group in the color image. In this way, the visible grayscale of the monochromatized image may be made similar to the visible grayscale of the color image. Thus, visual discomfort that a user feels when the user looks at a monochrome image converted from a color image may be reduced. 
     While the first embodiment has been described with reference to an operation in which a numerical range between the lowest value and the highest value of the theoretical density determined in accordance with the number of bits of the density value is separated into the numerical ranges corresponding to the m color groups, the operation is not limited thereto. For example, if the densities of the representative colors of the color groups differ from one another by a certain value or more, the densities of the representative colors of the color groups may be directly assigned to the color groups. 
     In addition, while the second embodiment has been described with reference to an operation in which screen patterns that have at least one of different halftone dot area ratios, different numbers of lines of halftone dots, different shapes of a pattern, and different angles of a pattern arrangement are assigned to the color groups, the operation is not limited thereto. For example, screen patterns that have at least one of different shapes of a pattern and different angles of a pattern arrangement may be assigned to the color groups, and the halftone dot area ratio of the screen patterns assigned to the color groups may be varied in accordance with the densities of the representative colors of the color groups. 
     Furthermore, for example, if the color groups have the same hue but different color values, such as dark red and light read, in the original color image, a screen pattern having the same number of lines or the same pattern is assigned to the color groups having the same hue. In addition, the halftone dot area ratio may be varied in accordance with the density of the representative color of each of the color groups. By assigning the screen patterns to the color groups in this manner, the appearance of the converted monochrome image may be made more similar to the appearance of the unconverted color image. The present technology also embraces such an embodiment. 
     In addition, while the second embodiment has been described with reference to a halftone dot screen pattern, the present technology is not limited thereto. For example, any patterns that are recognized as different patterns in a monochrome image may be employed. Accordingly, for example, screen patterns illustrated in  FIGS. 10A to 10F  may be employed. A screen pattern  130  illustrated in  FIG. 10A  is a pattern having diagonally right down lines arranged at certain intervals. A screen pattern  132  illustrated in  FIG. 10B  is a pattern having diagonally right up lines arranged at certain intervals. In addition, a screen pattern  134  illustrated in  FIG. 10C  is a pattern having vertical lines arranged at certain intervals. A screen pattern  136  illustrated in  FIG. 10D  is a pattern having diagonally right up lines that are thicker than the lines of the screen pattern  132  and that are arranged at certain intervals. A screen pattern  138  illustrated in  FIG. 10E  is a pattern having wavy lines extending in the horizontal direction and arranged at certain intervals. A screen pattern  140  illustrated in  FIG. 10F  is a pattern having alternately arranged rectangular black regions and rectangular white regions. 
     Since the screen patterns  130  to  140  illustrated in  FIGS. 10A to 10F  are also recognized as different patterns in a monochrome image, these screen patterns may be stored in the storage unit  36  and, thereafter, as many of the screen patterns as the number of the color groups may be selectively used. Note that the screen patterns employed in the second embodiment are not limited to the above-described screen patterns. For example, screen patterns having different types of lines, such as solid lines, dotted lines, alternate long and short dash lines, wavy lines, and heavy lines, may be employed. 
     While the above-described embodiments have been described with reference to an operation in which the density of the representative color of each of the color groups is computed and the density or the screen pattern assigned to the color group is determined on the basis of a greater-lesser relationship between the computed densities, the operation is not limited thereto. For example, the present technology may embrace an embodiment in which the brightness of the representative color of each of the color groups is computed and the density or the screen pattern assigned to the color group is determined on the basis of a greater-lesser relationship among the computed brightness values. 
     While the above-described embodiments have been described with reference to the embodiments including the extracting unit  14 , the monochromatizing unit  22 , and the combining unit  24 , the present technology is not limited thereto. For example, if the acquiring unit  12  acquires only color images that do not include a natural image region, the extracting unit  14 , the monochromatizing unit  22 , and the combining unit  24  may be removed. 
     Alternatively, a user may input the information indicating whether the extracting unit  14 , the monochromatizing unit  22 , and the combining unit  24  operate. For example, when only the mood of an overall image of graphic pattern is desired (e.g., when a ready-for-the-press plate image for checking a draft is output), the user may input an instruction to stop the operations of the extracting unit  14 , the monochromatizing unit  22 , and the combining unit  24 . For example, if the user selects output in a high-resolution mode, the extracting unit  14 , the monochromatizing unit  22 , and the combining unit  24  operate. However, if the user selects output in a low-resolution mode (or a high-speed mode), the extracting unit  14 , the monochromatizing unit  22 , and the combining unit  24  do not operate. 
     If the extracting unit  14 , the monochromatizing unit  22 , and the combining unit  24  do not operate, a color image acquired by the acquiring unit  12  is input to the separating unit  16 . The operations of the separating unit  16  and the computing unit  18  are the same as those in the first embodiment. Thereafter, the conversion unit  20  outputs the processing result to the output unit  26  instead of the combining unit  24 . 
     While the above-described embodiments have been described with reference to the operation in which different densities are assigned to the pixel groups of the monochrome image included in different color groups and an operation in which different types of grayscale (different screen patterns) are assigned to the pixel groups of the monochrome image included in different color groups, the present technology is not limited thereto. For example, different densities and different types of grayscale may be assigned to the pixel groups of the monochrome image included in different color groups. 
     While the above-described embodiments have been described with reference to the processing technique in which the color distribution of the pixels is separated into a plurality of color groups by the separating unit  16  that allocates a currently processed pixel to a color group having a minimum color difference from the color of the pixel and repeats such a process for each of the pixels, the present technology is not limited thereto. Any separating unit  16  that converts a color used in a color image to be processed to a different color may be used. That is, the separating unit  16  may group the pixels having similar pixel values into the same color group on the basis of the similarity between the pixel values. For example, the pixels are plotted in the color coordinates on the basis of the values of the pixels of the image data, and the plotted pixels in a certain range are defined as a color group. That is, the pixels may be separated into color groups on the basis of the color distribution in the color coordinates. In such a case, the value indicating the certain range may be certain as described in the first embodiment. Alternatively, for example, by using the pixel values of the pixels, a histogram indicating the color distribution may be generated. The color distribution may be separated at the turning point of the generated histogram (at the point at which the frequency is minimized). Thus, the color distribution of the pixels of the image may be separated into a plurality of color groups. 
     In addition, the operation in process  88  may be changed as follows. That is, a pixel that is to be temporarily processed is selected from among the currently processed pixel received in operation  72  and the pixels registered in the pixel list. Thereafter, from among the representative colors registered in the pixel list, the representative color having a minimum color difference within the range in which the representative color is regarded as the color of the temporarily selected pixel may be searched for. The range in which the representative color is regarded as the color of the temporarily selected pixel may be determined as in operation  76 . In such a case, in operation  90 , the information regarding the pixel that is to be temporarily processed is additionally registered in the record of the pixel list in which the representative color extracted in operation  88  is registered. 
     If, in operation  88 , the pixel that is to be temporarily processed is the currently processed pixel read in operation  72 , the information regarding the pixel that is to be temporarily processed, in operation  90 , is additionally registered in the record of the pixel list in which the representative color extracted in operation  88  is registered, as in the above-described operation  82 . However, if, in operation  88 , the pixel that is to be temporarily processed is not the currently processed pixel read in operation  72 , that is, if the pixel that is to be temporarily processed is a pixel registered in the pixel list, the information regarding the pixel that is to be temporarily processed, in operation  90 , is moved into the record in which the representative color extracted in operation  88  is registered. 
     Alternatively, for example, the color distribution of the pixels of the image may be separated into a plurality of color groups using a median cut algorithm. In the median cut algorithm, a rectangular parallelepiped that is circumscribed around the color distribution in the RGB space of the original image is defined first. Thereafter, the rectangular parallelepiped is divided such that all of the pixels of the original image are divided into two equal parts by an axis that is parallel to the longest side of the rectangular parallelepiped. By repeating such an operation, the rectangular parallelepiped is divided into small pieces. Finally, N rectangular parallelepipeds each including the same number of pixels are generated. The average of the color data items in each of the rectangular parallelepipeds is defined as a representative color. Note that the axis that divides a rectangular parallelepiped into two pieces may be an axis having the largest variance instead of the longest axis. 
     All examples and conditional language recited herein are intended for pedagogical purposes to aid the reader in understanding the invention and the concepts contributed by the inventor to furthering the art, and are to be construed as being without limitation to such specifically recited examples and conditions, nor does the organization of such examples in the specification relate to a showing of the superiority and inferiority of the invention. Although the embodiments of the present invention have been described in detail, it should be understood that the various changes, substitutions, and alterations could be made hereto without departing from the spirit and scope of the invention.