Patent Publication Number: US-10783390-B2

Title: Recording medium recording character area extraction program, information processing apparatus and character area extraction method

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is based upon and claims the benefit of priority of the prior Japanese Patent Application No. 2017-225029, filed on Nov. 22, 2017, the entire contents of which are incorporated herein by reference. 
     FIELD 
     The embodiments discussed herein are related to a recording medium for recording a character area extraction program, an information processing apparatus, and a character area extraction method. 
     BACKGROUND 
     In a character recognition processing, an area (character area) including characters (e.g., characters written on a signboard or sign) is extracted from, for example, a photographed image captured by an image capturing device. Character recognition is performed with respect to the extracted character area. 
     Related technologies are disclosed in, for example, Japanese Laid-open Patent Publication No. 2012-108689. 
     SUMMARY 
     According to one aspect of the embodiments, a non-transitory computer-readable recording medium recording a character area extraction program for causing a computer to execute a process includes: changing a relationship in relative sizes between an image and a scanning window that scans the image; scanning the scanning window based on a changed relationship; specifying a scanning position at which an edge density of an image area included in the scanning window is equal to or larger than a threshold value; extracting one or more areas indicated by the scanning window at the specified scanning position as one or more character area candidates; determining, when overlapped character area candidates included in the one or more character area candidates overlap with each other, a maximum character area candidate having a maximum edge density among the overlapped character area candidates; and extracting the image area included in the maximum character area candidate as a character area. 
     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  illustrates an example of an image processing system; 
         FIG. 2  illustrates an example of a hardware configuration of an image processing apparatus; 
         FIG. 3  illustrates an example of a functional configuration of a character area extracting unit; 
         FIGS. 4A and 4B  illustrate an example of a relationship between resolution and edge density; 
         FIG. 5  illustrates an example of a character area candidate extraction processing; 
         FIG. 6  illustrates an example of an overlapping area extraction processing and a character area determination processing; 
         FIG. 7  illustrates an example of a character area extraction processing; 
         FIG. 8  illustrates an example of the character area extraction processing; and 
         FIG. 9  illustrates an example of the character area extraction processing. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     In a character recognition processing, it is required that character areas are extracted from, for example, captured images without excess or deficiency. However, in the case of characters included in, for example, the captured images, the sizes of characters are not standardized. For this reason, a plurality of characters having different sizes is included. Therefore, an unextracted character area may occur. 
     For example, a plurality of images with different resolutions is generated. Candidates of the character areas are detected from images of the plurality of respective resolutions. An area in which the detected character area candidates overlap for more than a predetermined number is extracted as the character area. 
     According to the extraction method, even in a case where a plurality of characters having different sizes is included, respective character areas may be extracted. 
     For example, in the extraction method, the extracted character area includes many background images other than characters. For example, an area wider than an area where characters actually exist is extracted as the character area. Therefore, an extraction accuracy (a ratio of the area in which the characters are actually present, which is occupied in the extracted character area) is low. Therefore, when the character recognition is performed using the extracted character area, the character recognition accuracy may decrease. 
     For example, a technique may be provided, which enhances the extraction accuracy when extracting the character area from an image. 
     In the present specification and the drawings, components having a substantially similar functional configuration will be denoted with the same reference numeral, and overlapping descriptions thereof will be omitted. 
     First Embodiment 
     &lt;System Configuration of Image Processing System&gt; 
       FIG. 1  illustrates an example of an image processing system. 
     As illustrated in  FIG. 1 , the image processing system  100  includes an image providing apparatus  110 , an image processing apparatus  120 , and a terminal  130 . The image providing apparatus  110  is connected to the image processing apparatus  120  via a wired or wireless network (or the image providing apparatus  110  is directly set in a drive device of the image processing apparatus  120 ). The image processing apparatus  120  and the terminal  130  are connected to each other via a network  140 . 
     The image providing apparatus  110  is an apparatus or a medium that provides image data such as captured images to the image processing apparatus  120 , and in the first embodiment, the image providing apparatus  110  includes an imaging apparatus  111  and various recording media  112 . The recording medium  112  is a medium capable of storing the image data, and the recording medium  112  includes a predetermined medium. 
     The image processing apparatus  120  is an example of a character area extraction apparatus. An image acquisition program and a character area extraction program are installed in the image processing apparatus  120 , and when the program is executed, the image processing apparatus  120  serves as an image acquisition unit  121  and a character area extracting unit  122 . 
     The image acquisition unit  121  acquires the image data from the image providing apparatus  110  and stores the acquired image data in an image storage unit  123 . The character area extracting unit  122  reads out the image data stored in the image storage unit  123  and extracts the character area in each frame included in the image data. The character area extracting unit  122  transmits the extracted character area together with the image data to the terminal  130  via the network  140 . 
     The terminal  130  receives the image data transmitted from the character area extracting unit  122  via the network  140  and performs a character recognition processing with respect to the character area in each frame included in the image data. The terminal  130  outputs a result of the character recognition processing. 
     &lt;Hardware Configuration of Image Processing Apparatus&gt; 
       FIG. 2  illustrates an example of a hardware configuration of an image processing apparatus. As illustrated in  FIG. 2 , the image processing apparatus  120  includes a CPU (central processing unit)  201 , a read only memory (ROM)  202 , and a random access memory (RAM)  203 . The CPU  201 , the ROM  202 , and the RAM  203  form a so-called computer. 
     The image processing apparatus  120  includes an auxiliary storage device  204 , a display device  205 , an operation device  206 , an interface (I/F) device  207 , a communication device  208 , and a drive device  209 . Further, the respective hardware components of the image processing apparatus  120  are connected to each other via a bus  210 . 
     The CPU  201  is an arithmetic device that executes various programs (e.g., image acquisition program and character area extraction program) installed in the auxiliary storage device  204 . 
     The ROM  202  is a nonvolatile memory. The ROM  202  serves as a main storage device for storing, for example, various programs and data which the CPU  201  requires to execute the various programs installed in the auxiliary storage device  204 . For example, the ROM  202  functions as a main storage device for storing, for example, a boot program, such as a basic input/output system (BIOS) or an extensible firmware interface (EFI). 
     The RAM  203  is a volatile memory such as a dynamic random access memory (DRAM) or a static random access memory (SRAM). The RAM  203  serves as a main storage device for providing a working area developed when various programs installed in the auxiliary storage device  204  are executed by the CPU  201 . 
     The auxiliary storage device  204  is an auxiliary storage device that stores, for example, various programs and image data processed by execution of various programs. For example, the image storage unit  123  is implemented by the auxiliary storage device  204 . 
     The display device  205  is a display device for displaying, for example, an internal state of the image processing apparatus  120 . The operation device  206  is an input device for an administrator of the image processing apparatus  120  to input various instructions to the image processing apparatus  120 . 
     The I/F device  207  is a connection device for connecting with, for example, the imaging apparatus  111  in the image providing apparatus  110 . The communication device  208  is a communication device for communicating with the terminal  130  via the network  140 . 
     The drive device  209  is a device for setting, for example, the recording medium  112  in the image providing apparatus  110 . The recording medium  112  referred to here includes, for example, a medium that optically, electrically, or magnetically records information, such as a CD-ROM, a flexible disk or a magneto-optical disk. The recording medium  112  may include, for example, a semiconductor memory for electrically recording information, such as, for example, a ROM, or a flash memory. 
     The drive device  209  may be used when installing various programs in the auxiliary storage device  204 . For example, an administrator of the image processing apparatus  120  sets the distributed recording medium  112  in the drive device  209  to allow the driver device  209  to read out various programs recorded in the recording medium  112 , so that various kinds of programs may be installed in the auxiliary storage device  204 . 
     Alternatively, installation of various programs in the auxiliary storage device  204  may be performed via the communication device  208 . For example, the administrator of the image processing apparatus  120  may download various programs from the network  140  via the communication device  208 , so that various programs may be installed in the auxiliary storage device  204 . 
     &lt;Functional Configuration of Character Area Extracting Unit&gt; 
       FIG. 3  illustrates an example of a functional configuration of a character area extracting unit. 
     As illustrated in  FIG. 3 , the character area extracting unit  122  includes an image read-out unit  301 , a relative size changing unit  302 , a scanning unit  303 , a character area candidate extracting unit  304 , an overlapping area extracting unit  305 , a character area determining unit  306 , and an output unit  307 . 
     The image read-out unit  301  reads out the image data stored in the image storage unit  123  for each frame and notifies the read-out image data to the relative size changing unit  302 . 
     The relative size changing unit  302  is an example of a changing means and changes the resolution with respect to the notified image data having a unit of frame. The relative size changing unit  302  sequentially changes the resolution on the basis of a predetermined change pattern to sequentially change the relationship of a relative size between the image data and a scanning window having a fixed size. 
     For example, the relative size changing unit  302  sequentially changes the vertical resolution in a state where the horizontal resolution of the image data is fixed to a predetermined resolution. When the change of the vertical resolution is completed for a predetermined change range, the relative size changing unit  302  continuously fixes the horizontal resolution of the image data to another resolution and similarly changes the vertical resolution in sequence. The relative size changing unit  302  repeats the processing and achieves a combination of all of the vertical and horizontal resolutions by completing a change of a predetermined change range with respect to the horizontal resolution. 
     Every time the resolution of the image data is changed based on the predetermined change pattern, the scanning unit  303  scans the image data of the resolution after the change by using the fixed size scanning window. The scanning unit  303  extracts an image area included in the scanning window at each scanning position and notifies the extracted image area to the character area candidate extracting unit  304 . 
     The character area candidate extracting unit  304  is an example of an extraction means and extracts edge pixels from the image area included in the scanning window and calculates the edge density of the image area. The edge density refers to a ratio of the number of pixels of the edge pixel to the total number of pixels of the image area included in the scanning window. 
     The character area candidate extracting unit  304  specifies a scanning position at which the calculated edge density is equal to or larger than a predetermined threshold value and extracts an area indicated by the scanning window at a specified scanning position as a character area candidate. Furthermore, the character area candidate extracting unit  304  notifies the extracted character area candidate to the overlapping area extracting unit  305  together with the (vertical and horizontal) resolution at that time. 
     The overlapping area extracting unit  305  enlarges or reduces the character area candidate notified from the character area candidate extracting unit  304 . For example, the overlapping area extracting unit  305  calculates an enlargement ratio or a reduction ratio when enlarging or reducing the image data from which each character area candidate is extracted to image data of unified resolution, and enlarges or reduces the character area candidate. 
     The overlapping area extracting unit  305  arranges the enlarged or reduced character area candidates in the image data of unified resolution. Further, the overlapping area extracting unit  305  determines whether the character area candidates overlap with each other in a predetermined threshold area or more with respect to the image data in which the enlarged or reduced character area candidate is arranged. When it is determined that the character area candidates overlap with each other in the predetermined threshold area or more, the overlapping area extracting unit  305  extracts overlapping character area candidates and associates the extracted character area candidates with each other. 
     The character area determining unit  306  is an example of a determination unit, and determines a character area candidate having maximum edge density from the character area candidates associated by the overlapping area extracting unit  305 . The character area determining unit  306  extracts the image area included in the determined character area candidate as the character area. 
     The output unit  307  outputs the character area extracted by the character area determining unit  306  in association with the image data of a processing target frame. 
     &lt;Relationship of Resolution and Edge Density&gt; 
     The relationship between the image data with the changed resolution and the edge density of the image area included in the scanning window at each scanning position in the image data of each resolution will be described.  FIGS. 4A and 4B  illustrate an example of a relationship between resolution and edge density. 
       FIG. 4A  illustrates each image data when vertical resolution is sequentially changed in a state where horizontal resolution of image data is fixed to predetermined resolution and edge density of an image area included in a scanning window at a predetermined scanning position in the image data of each resolution. 
     Each image data illustrated in  FIG. 4A  is displayed by fixing the size of the pixel. Therefore, in each image data illustrated in  FIG. 4A , the vertical size is displayed larger as the vertical resolution becomes higher. 
     As illustrated in  FIG. 4A , in the case of image data  402  having a higher vertical resolution than that of image data  401 , the edge density of the image area included in the fixed-size scanning window  400  is higher than that in the case of the image data  401 . Similarly, in the case of image data  403  having higher vertical resolution than the image data  402 , the edge density of the image area included in the fixed-size scanning window  400  is higher than that in the case of the image data  402 . Similarly, in the case of image data  404  having higher vertical resolution than the image data  403 , the edge density of the image area included in the fixed-size scanning window  400  is higher than that in the case of the image data  403 . Meanwhile, in the case of image data  405  having higher vertical resolution than the image data  404 , the edge density of the image area included in the fixed-size scanning window  400  is lower than in the case of the image data  404 . 
     As described above, the edge density of the image area included in the fixed-size scanning window  400  is maximized in a state in which the characters in the image area are vertically inscribed in the fixed-size scanning window  400 . 
       FIG. 4B  illustrates each image data in a case where the horizontal resolution is sequentially changed in a state where vertical resolution of image data is fixed to predetermined resolution, and an edge density of an image area included in a scanning window at a predetermined scanning position in the image data of each resolution. 
     Similarly to  FIG. 4A , each image data illustrated in  FIG. 4B  is also displayed by fixing the size of the pixel. Therefore, in each image data illustrated in  FIG. 4B , the horizontal size is displayed larger as the horizontal resolution becomes higher. 
     As illustrated in  FIG. 4B , in the case of image data  412  having higher horizontal resolution than image data  411 , the edge density of the image area included in the fixed-size scanning window  400  is higher than in the case of the image data  411 . Similarly, in the case of image data  413  having higher horizontal resolution than the image data  412 , the edge density of the image area included in the fixed-size scanning window  400  is higher than in the case of the image data  412 . Similarly, in the case of image data  414  having higher horizontal resolution than the image data  413 , the edge density of the image area included in the fixed-size scanning window  400  is higher than in the case of the image data  413 . Meanwhile, in the case of image data  415  having a higher horizontal resolution than that of the image data  414 , the edge density of the image area included in the fixed-size scanning window  400  is lower than in the case of the image data  414 . 
     As described above, the edge density of the image area included in the fixed-size scanning window  400  is maximized in a state in which the characters in the image area are horizontally inscribed in the fixed-size scanning window  400 . 
     Therefore, by sequentially changing the vertical and horizontal resolution of the image data and determining the resolution at which the edge density becomes the maximum, it is possible to extract an image area in which the characters are inscribed in the scanning window in the vertical direction and the horizontal direction. That is, it is possible to extract character areas with high extraction accuracy, in which background images other than the characters are excluded as much as possible. 
     &lt;Overview of Character Area Candidate Extraction Processing&gt; 
     The character area candidate extracting unit  304  performs the character area candidate extraction processing.  FIG. 5  illustrates an example of the character area candidate extraction processing. As described above, the relative size changing unit  302  generates image data of an arbitrary combination of all resolutions within a predetermined change range in the vertical direction and all resolutions within a predetermined change range in the horizontal direction. However, in  FIG. 5 , for simplicity of description, only a combination of some of the resolutions is excerpted and represented. The scanning unit  303  performs scanning using the scanning window  400  with respect to all of the areas in the image data whose resolution is changed, but here, the scanning unit  303  will be described by considering a scanning position at which a predetermined character “523” is drawn in the image data. 
     When the position at which the predetermined character “523” in the image data is drawn becomes the scanning position, the edge density calculated by the character area candidate extracting unit  304  is changed with the change of the vertical resolution of the image data as illustrated in (a) of  FIG. 5 . 
     Among them, image data  403  to  405  in which the edge density is equal to or larger than a predetermined threshold value Th 1  are considered. With respect to the vertical resolutions of the respective image data  403  to  405 , when five image data having different horizontal resolutions from each other are excerpted to make the edge density into a graph, the edge density is illustrated in (b- 1 ) to (b- 3 ) of  FIG. 5 . 
     As illustrated in respective (b- 1 ) to (b- 3 ) of  FIG. 5 , image data (e.g., image data  521  to  542 ) other than the image data  403  to  405  among five image data having different horizontal resolutions have higher edge density than the image data  403  to  405 . 
     The character area candidate extracting unit  304  specifies image data  521 ,  531 , and  541  having a resolution in which the edge density is equal to or larger than a predetermined threshold value Th 2  among the image data. The character area candidate extracting unit  304  extracts the area indicated by the scanning window  400  for the specified image data  521 ,  531 , and  541  as character area candidates  551 ,  552 , and  553 . 
     &lt;Overview of Overlapping Area Extraction Processing and Character Area Determination Processing&gt; 
     The overlapping area extracting unit  305  performs the overlapping area extraction processing, and the character area determining unit  306  performs the character area determination processing.  FIG. 6  illustrates an example of the overlapping area extraction processing and the character area determination processing. 
     As illustrated in  FIG. 6 , the overlapping area extracting unit  305  enlarges or reduces the sizes of the character area candidates  551 ,  552 , and  553  extracted from the image data  521 ,  531 , and  541 . 
     For example, the overlapping area extracting unit  305  calculates the enlargement ratio or the reduction ratio when enlarging or reducing the image data  521 ,  531 , and  541  to image data  521 ′,  531 ′, and  541 ′ of unified resolution. For example, the overlapping area extracting unit  305  calculates the enlargement ratio when enlarging the image data  521  to the image data  521 ′, and enlarges the character area candidate  551  using the enlargement ratio to obtain a character area candidate  551 ′. The overlapping area extracting unit  305  calculates the enlargement ratio when enlarging the image data  531  to the image data  531 ′, and enlarges the character area candidate  552  using the enlargement ratio to obtain a character area candidate  552 ′. Further, the overlapping area extracting unit  305  calculates the reduction ratio when reducing the image data  541  to the image data  541 ′ and reduces the character area candidate  553  using the reduction ratio to obtain a character area candidate  553 ′. 
     Subsequently, the overlapping area extracting unit  305  arranges the enlarged or reduced character area candidates  551 ′,  552 ′, and  553 ′ in the unified resolution image data (here, the image data  531 ′) to determine whether overlapping occurs. 
     In the case of the example of  FIG. 6 , since the character area candidates  551 ′,  552 ′, and  553 ′ overlap with each other in a predetermined threshold area or more, the overlapping area extracting unit  305  determines that the character area candidates  551 ′,  552 ′, and  553 ′ overlap with each other and extracts the character area candidates. The overlapping area extracting unit  305  associates the extracted character area candidates with each other. 
     The character area determining unit  306  determines a character area candidate having maximum edge density among the character area candidates  551 ′,  552 ′, and  553 ′ associated by the overlapping area extracting unit  305 . The example of  FIG. 6  indicates that it is determined that the edge density of the image area included in the character area candidate  552 ′ among the character area candidates  551 ′,  552 ′, and  553 ′ becomes the maximum. 
     &lt;Flow of Character Area Extraction Processing&gt; 
     The character area extracting unit  122  performs a character area extraction processing.  FIGS. 7 to 9  illustrate an example of the character area extraction processing. 
     In step S 701 , the image read-out unit  301  reads out image data  900  ( FIG. 9 ) of the processing target frame from the image storage unit  123 . In step S 702 , the scanning unit  303  reads out the fixed-size scanning window  400 . 
     In step S 703 , the relative size changing unit  302  initializes the vertical resolution and the horizontal resolution to predetermined resolution with respect to the read-out image data  900 . 
     In step S 704 , the relative size changing unit  302  changes the vertical resolution in a state where the horizontal resolution is fixed with respect to the image data whose resolution is initialized. 
     In step S 705 , the scanning unit  303  scans the image data whose vertical resolution is changed in step S 703  using the fixed-size scanning window  400 . 
     In step S 706 , the character area candidate extracting unit  304  performs an edge processing on the image area at each scanning position of the scanning window  400  performing scanning to detect edge pixels. The character area candidate extracting unit  304  calculates the edge density of the image area at each scanning position based on the detected edge pixels, thereby specifying the scanning position having the edge density equal to or larger than the predetermined threshold value Th 2 . Furthermore, the character area candidate extracting unit  304  extracts the area indicated by the scanning window at the specified scanning position as the character area candidate. 
     In step S 707 , the character area candidate extracting unit  304  associates and maintains the extracted character area candidate with the edge density and the (vertical and horizontal) resolutions. 
     In step S 708 , the relative size changing unit  302  determines whether all vertical resolutions in a predetermined change range have been covered. When it is determined in step S 708  that all the vertical resolutions have not been covered (in the case of “No” in step S 708 ), the process returns to step S 704 . Meanwhile, when it is determined in step S 708  that all the vertical resolutions in the predetermined change range have been covered (in the case of “Yes” in step S 708 ), the process proceeds to step S 709 . 
     In step S 709 , the relative size changing unit  302  determines whether to all horizontal resolutions in the predetermined change range have been covered. When it is determined in step S 709  that all the horizontal resolution have not been covered (in the case of “No” in step S 709 ), the process proceeds to step S 710 . 
     In step S 710 , the relative size changing unit  302  initializes the vertical resolution to the predetermined resolution. In step S 711 , the relative size changing unit  302  changes the horizontal resolution, and the process proceeds to step S 704 . 
     As a result, in a state in which the horizontal resolution is fixed to the horizontal resolution newly changed in step S 711 , the scanning window  400  is scanned while sequentially changing the vertical resolution in steps S 704  to S 708  to extract the character area candidates. 
     In  FIG. 9 , image data  910  represents image data in a predetermined vertical resolution when scanning the scanning window  400  while changing the vertical resolution in step S 704  in a state the newly changed horizontal resolution is fixed in step S 711 . In the case of the image data  910 , the scanning window  400  is scanned to extract character area candidates  911  and  912 . 
     Image data  920  represents image data in a predetermined vertical resolution when scanning the scanning window  400  while changing the vertical resolution in step S 704  in a state in which a further changed horizontal resolution is fixed in step S 711 . In the case of the image data  920 , the scanning window  400  is scanned to extract character area candidates  921 ,  922 , and  923 . 
     Image data  930  represents image data in a predetermined vertical resolution when scanning the scanning window  400  while changing the vertical resolution in step S 704  in a state a further changed horizontal resolution is fixed in step S 711 . In the case of the image data  930 , the scanning window  400  is scanned to extract character area candidates  931  and  932 . 
       FIG. 7  will be referred back. When it is determined in step S 709  that all the horizontal resolutions in the predetermined change range have been covered (in the case of “Yes” in step S 709 ), the process proceeds to step S 801  of  FIG. 8 . 
     In step S 801 , the overlapping area extracting unit  305  reads out the character area candidates  911 ,  912 ,  922 ,  923 ,  931 , and  932  held in step S 707 . The overlapping area extracting unit  305  calculates an enlargement ratio or a reduction ratio for rendering the resolution (vertical direction, horizontal direction) associated with the read-out character area candidate to a unified resolution. Further, based on the calculated enlargement ratio or reduction ratio, the overlapping area extracting unit  305  enlarges or reduces the character area candidates  911  to  932  and arranges the character area candidates  911  to  932  in the image data of the unified resolution. 
     In  FIG. 9 , image data  940  represents the image data of the unified resolution. Character area candidates  911 ′ to  932 ′ represent states in which the character area candidates  911  to  932  held in step S 707  are enlarged or reduced and arranged in the image data  940 , respectively. 
     For example, the character area candidate  911 ′ represents a state of the character area candidate  911  extracted from the image data  910 , which is enlarged based on the enlargement ratio of the image data  910  for the image data  940  and arranged in the image data  940 . The character area candidate  912 ′ represents a state of the character area candidate  912  extracted from the image data  910 , which is enlarged based on the enlargement ratio of the image data  910  for the image data  940  and arranged in the image data  940 . 
     Similarly, the character area candidate  921 ′ represents a state of the character area candidate  921  extracted from the image data  920  which is enlarged based on the enlargement ratio of the image data  920  for the image data  940  and arranged in the image data  940 . The character area candidate  922 ′ represents a state of the character area candidate  922  extracted from the image data  920 , which is enlarged based on the enlargement ratio of the image data  920  for the image data  940  and arranged in the image data  940 . The character area candidate  923 ′ represents a state of the character area candidate  923  extracted from the image data  920 , which is enlarged based on the enlargement ratio of the image data  920  for the image data  940  and arranged in the image data  940 . 
     Similarly, the character area candidate  931 ′ represents a state of the character area candidate  931  extracted from the image data  930  which is enlarged based on the enlargement ratio of the image data  930  for the image data  940  and arranged in the image data  940 . The character area candidate  932 ′ represents a state of the character area candidate  932  extracted from the image data  930 , which is enlarged based on the enlargement ratio of the image data  930  for the image data  940  and arranged in the image data  940 . 
       FIG. 8  will be referred back. In step S 802 , the overlapping area extracting unit  305  determines whether the character area candidates arranged in the image data of the unified resolution overlap with each other in a predetermined threshold area or more. When it is determined that the character area candidates overlap with each other in the predetermined threshold area or more, the overlapping area extracting unit  305  extracts overlapping character area candidates and associates the extracted character area candidates with each other. 
     Image data  950  of  FIG. 9  indicates that it is determined that the character area candidates  912 ′,  923 ′,  931 ′, and  932 ′ among the character area candidates  911 ′ to  932 ′ arranged in the image data  940  of the unified resolution overlap with each other and associated with each other. 
     In step S 803 , the character area determining unit  306  determines a character area candidate having the maximum edge density among character area candidates associated with each other. Image data  960  of  FIG. 9  indicates that it is determined that the edge density of the character area candidate  912 ′ is the maximum among the edge densities of the character area candidates  912 ′,  923 ′,  931 ′, and  932 ′ associated with each other. 
     In step S 804 , the character area determining unit  306  extracts the image area included in the character area candidate  912 ′ determined to have the maximum edge density as the character area. 
     As is apparent from the above description, the character area extracting device according to the first embodiment scans the image data of the frame to be processed while changing the resolution by using the fixed scanning window to specify each scanning position at which the edge density is equal to or larger than a predetermined threshold value. The character area extracting device according to the first embodiment extracts the area indicated by the scanning window as the character area candidate at each specific scanning position. The character area extracting device according to the first embodiment arranges the extracted character area candidates in the image data of the unified resolution and determines the character area candidate having the maximum edge density among the character area candidates which overlap with each other. Furthermore, the character area extracting device according to the first embodiment extracts the image area included in the determined character area candidate as the character area. 
     As described above, by extracting the character area based on the edge density, it is possible to extract the image area in which the characters are inscribed in the scanning window as the character area. That is, it is possible to extract character areas with high extraction accuracy, in which background images other than the characters are excluded as much as possible. 
     Second Embodiment 
     In the first embodiment, the relative size changing unit  302  has been described as sequentially changing the vertical resolution with the horizontal resolution fixed first, however, a changing order is not limited thereto. For example, the horizontal resolution may be sequentially changed while the vertical resolution is first fixed. 
     In the first embodiment, the character recognition processing is described as being executed in the terminal  130 , but the character recognition processing may be executed by the image processing apparatus  120 . In the first embodiment, it is described that the character area extraction processing is performed by the character area extracting unit  122  of the image processing apparatus  120 , but a part of the function of the character area extracting unit  122  may be installed in another device and executed by a plurality of apparatuses (e.g., by the system). The plurality of corresponding apparatuses may include the imaging apparatus  111  or the terminal  130 . 
     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 an illustrating 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.