Abstract:
An image forming apparatus which is composed of an image reading unit for reading a document image and converting the document image into image data, an image processing unit for applying image processes containing edge enhancing process and smoothing process to the image data, and an image forming unit for forming the processed image data on a printing medium. The image processing unit includes a halftone dot detector for detecting a halftone dot region using the image data, a first edge detector for executing edge detection over the detected halftone dot region using a derivative filter, and a second edge detector for executing edge detection over a non-halftone dot region other than the detected halftone dot region using a derivative filter with a size different from a size of the derivative filter.

Description:
This application is based on Japanese Patent Application No. 11-80426 filed on Mar. 24, 1999, the contents of which are hereby incorporated by reference. 
     BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The invention relates to an apparatus and a method for processing images, as well as to a storage medium carrying data generated by programming the method, in particular a filtering procedure for screened halftone images. 
     2. Description of Related Art 
     A majority of printed matters or documents today contain images expressed in numerous minute halftone dots, i.e., halftone images. When a document image scanned by a scanner is printed, the Moire effect may develop depending on the relation between the spatial frequency of the halftone dots contained in the document image and the dither pattern cycle. 
     The conventional digital copying machine applies the smoothing process to a halftone dot region to soften the edges of halftone dots in order to prevent the Moiré effect while applying the edge enhancing process to character elements in order to reproduce the character elements more sharply. However, such a method cannot be effective when character elements exist in the halftone dot region. For example, if the smoothing process is applied to the halftone dot region where character elements exist, the recreation capability for the character elements drops. On the other hand, if the enhancement process is applied to the same area, the edges of minute dots are enhanced, so that the Moiré effect may develop to deteriorate the image quality. 
     A method of detecting character elements in the halftone dot region by means of the spatial filter has been known. The size of the spatial filter is chosen to be larger than the spatial frequency of the halftone dots so that the edges of the halftone dots would not be mistaken as the edges of the character elements. Consequently, the edges of character elements in the non-halftone dot region, for example, the edges of fine letters written on a white background cannot be detected precisely, same as the edges of halftone dots so that the character elements cannot be sharply reproduced. 
     SUMMARY OF THE INVENTION 
     It is an object of the present invention to provide an image processing apparatus including a receiving unit for receiving image data, a halftone dot detector for detecting a halftone dot region using the received image data, a first edge detector for executing edge detection over the detected halftone dot region using a derivative filter, and a second edge detector for executing edge detection over a non-halftone dot region other than the detected halftone dot region using a derivative filter with a size different from a size of the derivative filter. 
     A further object of the invention is to provide an image reading apparatus including an image reading unit for reading a document image and converting the document image into image data, an image processing unit for applying image processes containing edge enhancing process and smoothing process to the image data, and a transmission unit for transmitting the processed image data. Furthermore, the image processing unit includes a halftone dot detector for detecting a halftone dot region using the image data, a first edge detector for executing edge detection over the detected halftone dot region using a derivative filter, and a second edge detector for executing edge detection over a non-halftone dot region other than the detected halftone dot region using a derivative filter with a size different from a size of the derivative filter. 
     Still a further object of the invention is to provide an image forming apparatus including an image reading unit for reading a document image and converting the document image into image data, an image processing unit for applying image processes containing edge enhancing process and smoothing process to the image data, and an image forming unit for forming the processed image data on a printing medium. In addition, the image processing unit includes a halftone dot detector for detecting a halftone dot region using the image data, a first edge detector for executing edge detection over the detected halftone dot region using a derivative filter, and a second edge detector for executing edge detection over a non-halftone dot region other than the detected halftone dot region using a derivative filter with a size different from a size of the derivative filter. 
     Still a further object of the invention is to provide an image processing apparatus including a receiving unit for receiving image data, a halftone dot detector for detecting a halftone dot region using the received image data, a first edge enhancing unit for applying edge enhancement process to the detected halftone dot region using a derivative filter, and a second edge enhancing unit for applying edge enhancement process to a non-halftone dot region other than the halftone dot region using a derivative filter with a size different from a size of the derivative filter. 
     Still a further object of the invention is to provide an image reading apparatus including an image reading unit for reading a document image and converting the document image into image data, an image processing unit for applying image processes containing edge enhancing process to the image data, and a transmission unit for transmitting the processed image data. In addition, the image processing unit includes a halftone dot detector for detecting a halftone dot region using the image data, a first edge enhancing unit for applying edge enhancement process to the detected halftone dot region using a derivative filter, and a second edge enhancing unit for applying edge enhancement process to a non-halftone dot region other than the halftone dot region using a derivative filter with a size different from a size of the derivative filter. 
     Still a further object of the invention is to provide an image forming apparatus including an image reading unit for reading a document image and converting the document image into image data, an image processing unit for applying image processes containing edge enhancing process to the image data, and an image forming unit for forming the processed image data on a printing medium. Furthermore, the image processing unit includes a halftone dot detector for detecting a halftone dot region using the image data, a first edge enhancing unit for applying edge enhancement process to the detected halftone dot region using a derivative filter, and a second edge enhancing unit for applying edge enhancement process to a non-halftone dot region other than the halftone dot region using a derivative filter with a size different from a size of the derivative filter. 
     Another object of the invention is to provide an image processing method including the steps of receiving image data, detecting a halftone dot region using the received image data, executing edge detection over the detected halftone dot region using a derivative filter, and executing edge detection over a non-halftone dot region other than the detected halftone dot region using a derivative filter with a size different from a size of the derivative filter. 
     A further object of the invention is to provide an image processing method including the steps of receiving image data, detecting a halftone dot region using the received image data, applying edge enhancement process to the detected halftone dot region using a derivative filter, and applying edge enhancement process to a non-halftone dot region other than the halftone dot region using a derivative filter with a size different from a size of the derivative filter. 
     Another object of the invention is to provide a storage medium carrying data generated by programming an image processing method including the steps of receiving image data, detecting a halftone dot region using the received image data, executing edge detection over the detected halftone dot region using a derivative filter, and executing edge detection over a non-halftone dot region other than the detected halftone dot region using a derivative filter with a size different from a size of the derivative filter. 
     A further object of the invention is to provide a storage medium carrying data generated by programming an image processing method including the steps of receiving image data, detecting a halftone dot region using the received image data, applying edge enhancement process to the detected halftone dot region using a derivative filter, and applying edge enhancement process to a non-halftone dot region other than the halftone dot region using a derivative filter with a size different from a size of the derivative filter. 
     The objects, characteristics, and advantages of this invention other than those set forth above will become apparent from the following detailed description of the preferred embodiments, which refers to the annexed drawings. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     FIG. 1 is a block diagram of a digital copying machine according to embodiment 1; 
     FIG. 2 is a block diagram of an image correction unit and a feature detection unit of an image processing unit of the digital copying machine; 
     FIG.  3 A and FIG. 3B are first and second filters used for edge detection in the feature detection unit; 
     FIG.  4 A and FIG. 4B show examples of edge detection applied to a halftone dot region where character elements exist and a non-halftone dot region where character elements exist using the second filter; 
     FIG.  5 A and FIG. 5B show examples of edge detection applied to a halftone dot region where character elements exist and a non-halftone dot region where character elements exist using the first filter; 
     FIG. 6 is a block diagram of a digital copying machine according to embodiment 2; 
     FIG. 7 is a block diagram of an image correction unit and a feature detection unit of an image processing unit of the digital copying machine; and 
     FIG.  8 A and FIG. 8B are first and second filters used for edge detection in the feature detection unit. 
    
    
     DETAILED DESCRIPTION OF THE EMBODIMENTS 
     The embodiments of this invention will be described below with reference to the accompanying drawings. 
     EMBODIMENT 1 
     The digital copying machine shown in FIG. 1 includes a scanning unit  80  for reading document images, an image processing unit  10 , and a print unit  90  for printing output data on papers. The image processing unit  10  contains a memory  11 , a LOG unit  12 , a color system conversion unit  13 , a UCR (under color removal)-BP (black paint) unit  14 , an image correction unit  15 , a resolution conversion unit  16 , a dither unit  17 , and a feature detection unit  18 . Since the basic control circuit and mechanical structure are similar to those of the conventional machine, their descriptions are omitted. 
     General operations of the image processing unit  10  are described following the flow of the image data. 
     First, RGB image data of the document outputted from the scanning unit  80  is stored in the memory  11 . The RGB image data is read from the memory  11  in synchronization with printing timing signal from the print unit  90 , and inputted into the LOG unit  12  and the feature detection unit  18 . 
     At the LOG unit  12  the RGB image data is logarithmically converted. The logarithmic data is inputted into the color system conversion unit  13  and converted into CMY image data. The CMY image data is inputted into the UCR-BP unit  14  and converted into CMYK image data. The CMYK image data is inputted into the image correction unit  15 . 
     At the feature detection unit  18 , the RGB image data is classified. The result of the classification is entered into the image correction unit  15 . 
     At the image correction unit  15 , the CMYK image data is treated with filtering process according to the classification result from the feature detection unit  18  in addition to conventional corrections such as the gamma correction. Next, the image data is inputted into the resolution conversion unit  16  to have its resolution converted. More specifically, the resolution of the image data is converted from 300 dpi×300 dpi, which is the reading resolution of the scanning unit  80 , to 2400 dpi×600 dpi, which is the resolution of the dither process table. The image data is entered into the dither unit  17  to be compared with the dither table to be binarized. In other words, multi value image data is converted into binary image data. The binary image data is inputted into the print unit  90  via a printer video interface (not shown). 
     Next, the feature detection unit  18 , into which the RGB image data read from the memory  11  is inputted similar to the LOG unit  12 , is described in detail. 
     The feature detection unit  18  includes a brightness calculation unit  181 , a halftone dot detector  182 , an edge detector  183  and a total judgment unit  188  as shown in FIG.  2 . Moreover, the edge detector  183  consists of a first filter  184 , a second filter  185 , a selector  186 , and an edge identifying unit  187 . The first and second filters  184  and  185  are ordinary second derivative filters called Laplacian filters and are used for detecting edges based on the brightness gradient. The size of the second filter  185  is greater than the first filter  184 . FIG.  3 A and FIG. 3B are examples of the first and second filters  184  and  185 , respectively. 
     When the brightness calculation unit  181  receives the RGB image data, it calculates the brightness V of each pixel of the RGB image data according to the following formula, where k 1 , k 2  and k 3  are constants: 
     
       
         
           V=k 
           1 
           ×R+k 
           2 
           ×G+k 
           3 
           ×B 
         
       
     
     Next, the brightness data is entered into the edge detector  183  as well as into the halftone dot detector  182 . 
     At the halftone dot detector  182 , it is judged whether each pixel is an isolated point based on the brightness data. If the difference between the brightness V i  of each of neighboring pixels and the brightness V 0  of a target pixel is greater than the specified threshold value V T  as shown in the formula below, the target pixel is identified as an isolated point: 
     
       
         ( V   i   −V   0 )&gt; V   T   
       
     
     wherein the symbol “i” is a positive integer between 1 through N that corresponds to the number of the neighboring pixels to be set. 
     Next, the number of pixels that are identified as isolated points existing in an area greater than an area used for the judgement of the isolated point is counted. For example, the area for counting may consist of 20 pixels×20 pixels. If the number of the isolated points is not less than a certain number, e.g., 30, the target pixel is identified as belonging to the halftone dot region and if the number of the isolated points is under the certain number, the target pixel is identified as belonging to the non-halftone dot region. In this way, every pixel is judged whether it belongs to the halftone dot region. 
     The judgment result is inputted into the total judgment unit  188  and the selector  186 . The judgment can also be executed by means of identifying a nonwhite background or a white background in lieu of the above-described method based on isolation points. 
     On the other hand, at the edge detector  183 , the brightness data from the brightness calculation unit  181  is entered into the filters  184 ,  185 . The outputs from the filters  184 ,  185  are inputted into the selector  186 . 
     The outputs of the filters  184  and  185 , which result from operations of the brightness of pixels within a specified area the center of which the target pixel is located and the coefficients of the filters  184  and  185 , represent gradients of brightness. For example, the output L of the second filter  185 , which is a matrix consisting of five rows and five columns as shown in FIG. 3B, for the 5 pixels×5 pixels is obtained from the following formula: 
     
       
           L =(4 ×V   33   −V   11   −V   15   −V   51   −V   55 )/4 
       
     
     wherein the numbers 33, 11, 15, 51 and 55 represent the position of each pixel. For example, V 33  is the brightness of the target pixel, which is located in the center, or the crossing point of the third row and the third column, of the matrix. The absolute value of the output L of a pixel that belongs to an edge segment is large, and the output L of a pixel that belongs to a non-halftone dot region is zero. 
     The selector  186  selects either the output of the first filter  184  or the output of the second filter  185  depending on the identification result of the halftone dot detector  182 . The selected output is inputted into the edge identifying unit  187 . More specifically, the output of the second filter  185 , which is the larger of the two, is selected if the target pixel is judged to belong to the halftone dot region, and the output of the first filter  184 , which is the smaller of the two, is selected if the target pixel is judged to belong to a non-halftone dot region. 
     The edge identifying unit  187  judges that a pixel belongs to a large brightness gradient segment, i.e., an edge segment, if the absolute value of the selected output is not less than the threshold value and that a pixel belongs to a non-edge segment, if the absolute value of the selected output is under the threshold value. The output result is inputted into the total judgment unit  188 . 
     The total judgment unit  188  classifies the target pixel to either the character, halftone, or flat element, depending on the detection results of the edge identifying unit  187  and the halftone dot detector  182 . The character element corresponds to a case where the target pixel belongs to the edge segment. The halftone element corresponds to a case where the target pixel belongs to the halftone dot region and the non-edge segment. The flat element corresponds to all other cases. The result of the classification is inputted into the image correction unit  15 . 
     Next, the image correction unit  15 , into which the CMYK image data from the UCR-BP unit  14  and the classification results from the feature detection unit  18  are inputted, is described below in detail. 
     The image correction unit  15  has a smoothing filter  151 , a pass-through circuit  152 , an edge enhancing circuit  153  and a selector  154 . The selector  154  receives the classification results of the feature detection unit  18 . 
     The CMYK image data is inputted into the selector  154  via the smoothing filter  151 , the pass-through circuit  152 , and the edge enhancing circuit  153 . The selector  154  selects either one of the outputs of the smoothing filter  151 , the pass-through circuit  152 , or the edge enhancing circuit  153  depending on the judgment result of the total judgment unit  188 . More specifically, the edge enhancing process is applied to the data that belong to the character elements. Data that belong to the halftone elements are smoothed in order to prevent the Moiré effect from occurring. The filtering process is not applied to data that belong to the flat elements. The selected output is sent to the print unit  90  via the resolution conversion unit  16 , the dither unit  17  and the printer video interface. 
     Next, the difference between the filters  184  and  185  used for edge detection is described below. 
     When the edge detection using the second filter  185 , which is the larger derivative filter, is applied to the halftone dot region, the halftone elements can be scarcely detected, while character elements in the halftone dot region can be detected with a high accuracy as shown in FIG.  4 A. On the other hand, if the same is applied to the non-halftone dot region where character elements exist, i.e., to a white background where characters are written, the detection accuracy of the character elements in the non-halftone dot region is not sufficient as shown in FIG.  4 B. 
     If the edge detection using the first filter, which is the smaller derivative filter, is applied to the halftone dot region, the halftone elements as well as the character elements can be detected at a high accuracy as shown in FIG.  5 A. On the other hand, if the same is applied to the non-halftone dot region, the character elements in the non-halftone dot region can be detected at a high accuracy as shown in FIG.  5 B. 
     There is a difference in the threshold value, which is used for the edge detection by the edge identifying unit  187 , between the first and second filters  184 ,  185 . Specifically, the first filter  184  is smaller than the second filter  185  and the Laplacian value of the former is also smaller than that of the latter, so that the threshold value of the former is also set lower than that of the latter. 
     In embodiment 1, image data is classified based on the edge detection result of the image data by means of the first and second filters, as well as the judgment whether the image data belongs to the halftone dot region. The filtering process will be applied to the image data that suits the classification. Specifically, the edge enhancing process will be applied to character elements of the non-halftone dot region and character elements of the halftone dot region, to reproduce details sharply. On the other hand, the smoothing process is applied to the halftone dot region excluding the character elements, i.e., the halftone elements, to prevent the Moire effect from occurring. 
     EMBODIMENT 2 
     The digital copying machine shown in FIG. 6 includes an image correction unit  25 , an error diffusion unit  26  and a feature detection unit  27  in the image processing unit  20 . Embodiment 2 differs from embodiment 1 in that respect. As some parts of this machine that perform functions similar to those of corresponding parts of embodiment 1 are identified with the same symbols respectively, descriptions of those parts are partially omitted here. 
     The outline of the image processing unit  20  is described following the flow of the image data. 
     First, RGB image data of the document outputted from the scanning unit  80  is stored in the memory  11 . The RGB image data is read from the memory  11  in synchronization with printing timing signal from the print unit  90 , and inputted into the LOG unit  12  and the feature detection unit  27 . 
     At the LOG unit  12  the RGB image data is logarithmically converted. The logarithmic data is inputted into the color system conversion unit  13  and converted into CMY image data. The CMY image data is inputted into the UCR-BP unit  14  and converted into CMYK image data. The CMYK image data is inputted into the image correction unit  25 . 
     At the feature detection unit  27  the RGB image data is classified. The result of the classification is entered into the image correction unit  25 . 
     At the image correction unit  25 , the CMYK image data is treated with filtering process according to the classification result from the feature detection unit  27  in addition to conventional corrections such as the gamma correction. Next, the image data is inputted into the error diffusion unit  26 . The multi-value image data is converted into a binary image data by means of the error diffusion process. The binary image data is inputted into the print unit  90  via a printer video interface (not shown). 
     The feature detection unit  27  and the image correction unit  25  are described in detail referring to FIG. 7 in the following. 
     The feature detection unit  27  has the brightness calculation unit  181  and the halftone dot detector  182 . The brightness calculation unit  181  calculates the brightness of the pixels of the RGB image data read from the memory  11  in synchronization with the print timing signal from the print unit  90  as in embodiment 1. Next, the brightness data is inputted into the halftone dot detector  182 . At the halftone dot detector  182 , the target pixel is judged whether it belongs to the halftone dot region based on the isolated point method. The result of the detection is inputted into the image correction unit  25 . 
     The image correction unit  25  has a selector  253 , a first filter  251 , and a second filter  252 . The detection result of the feature detection unit  27  is inputted into the selector  253 . 
     The first and second filters  251 ,  252  into which the image data from The UCR-BP unit  14  is inputted consist of the first derivative filer or the second derivative filter that are normally used for the edge enhancing process. The size of the second filter  252  is greater than the size of the first filter  251 . FIG.  8 A and FIG. 8B show examples of the first and second filters  251 ,  252 . The first and second filters  251 ,  252  are different from the first and second filters  184 ,  185  of embodiment 1 in terms of the coefficients. 
     When the first filter  251 , which is the smaller derivative filter in size, is applied to an image data that belongs to the non-halftone dot region, fine points and lines will be enhanced. Therefore, character elements in the non-halftone dot region, for example, letters written on a white background, will be reproduced sharply. On the other hand, when the second filter  252 , which is the larger derivative filter in size, is applied to an image data that belongs to the halftone dot region, halftone elements will be scarcely enhanced. In addition, character elements in the halftone dot region will be reproduced sharply. 
     After the edge enhancing process by the first and second filters  251  and  252 , both results are inputted into the selector  253 . 
     The selector  253  selects either one of the outputs of the first or second filters  251  or  252  based on the detection result of the feature detection unit  27  and transmits it to the error diffusion unit  26 . More specifically, it selects the output of the first filter  251 , which is the smaller of the two, if the image data belongs to the non-halftone dot region. In addition, it selects the output of the second filter  252 , which is the larger of the two, when the image data belongs to the halftone dot region. 
     According to embodiment 2, either one of the first and second filters is selected depending on the detection result whether the image data belongs to the halftone dot region. Consequently, while character elements of the halftone dot region are enhanced similar to character elements of the non-halftone dot region, enhancement of the halftone dot region can be suppressed. In other words, while details of character elements are reproduced sharply, the Moiré effect due to the relation between the space frequency of halftone dots and the scanning cycle is suppressed. 
     It is obvious that this invention is not limited to the particular embodiments shown and described above but may be variously changed and modified without departing from the technical concept of this invention. 
     In both embodiments 1 and 2, one of the outputs of the filters is selected by the selector located on the downstream side of the filters. However, it is possible to input the image data into one of the filters selected by a selector placed on the upstream side of the filters. 
     The size of the filter does not necessarily have to be a fixed type, but rather can be set up as a variable type. Moreover, the number of filters does not have to be limited to two, but rather various sizes of filters can be used as well. 
     Moreover, although embodiments 1 and 2 are described concerning digital copying machines as an application example, the invention can be also applied to image reading apparatuses for reading document images such as scanners, or computers such as personal computers. Specifically, the image reading apparatuses can be integrated with similar units as the image processing units of embodiments 1 and 2. In case of computers, a storage medium that carrying data generated by programming the operating procedure of the image processing unit can be provided.