Abstract:
In one aspect, an image processing apparatus inputs an input image signal and detecting whether or not there is a frame change in an image by comparing the input image signal with a reference image signal. A memory is used for updating the reference image signal by storing the input image signal as the reference image signal in units of frames when there is a frame change. In another aspect, the image processing apparatus extracts change components between images by comparing the input image signal with the reference image signal, the reference image signal being an earlier input signal when a most recent prior change component was extracted. The extracted change components are corrected by detecting and removing an erroneously extracted change component, and an image change is discriminated in the input image signal on the basis of the change components as corrected.

Description:
BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The present invention relates to a motion image processing apparatus and method and, more particularly, to an image processing apparatus and method which can reduce transmission, storage, and display data amounts by detecting an image change and can be suitably used for an image transmission apparatus, an image storage device, and a motion image display device. That is, the present invention can be used for a monitoring apparatus for transmitting and storing images in a monitoring area, a video conference apparatus, a general-purpose computer or video server which handles motion images, and the like. 
     2. Related Background Art 
     In the field of monitoring, e.g., road monitoring and night monitoring, apparatuses which reduce the cost for monitoring by transmitting and monitoring images obtained by photographing a monitoring area with a TV camera or storing the images in a storage device have been used. In this case, the transmission and storage data amounts are reduced by detecting an image change and outputting image data only when an image change occurs. 
     In recent years, image data are exchanged and stored between remote places via a communication network such as a WAN (Wide Area Network) or a LAN (Local Area Network) in many instances, like a video conference, without the intention of monitoring. In addition, with an improvement in the performance of a general-purpose computer, the computer can transmit and store motion images as well as displaying motion images. 
     Since image data amounts too much, a dedicated device is required to perform detection processing an image change at a speed as high as that of image processing. If there is no such a dedicated device, an image temporarily stored is processed for a long period of time. 
     Recently, however, image data is transmitted, stored, or displayed by using a general-purpose computer in many instances. For example, video conference systems using general-purpose computers have become popular, as described above. Demands have therefore arisen for a method of performing detection processing of an image change at a speed as high as that of image processing without using any dedicated device. 
     Various methods associated with the above image change detection method have been proposed. A relatively easy method is a method of detecting a change area by obtaining a difference between two images. According to this easy method, even a general-purpose computer can execute detection processing at a sufficient processing speed. 
     As methods of detecting a change area on the basis of a difference between two images, typical methods are a method of detecting a change area on the basis of a difference between a background image photographed in advance and a currently photographed image, and a method of detecting a change area on the basis of a difference between two frames adjacent to each other along the time base. 
     There has been proposed an apparatus based on the latter method of detecting a change area on the basis of a difference between frames to record images in a monitoring area on a VTR, wherein an image change is detected and an image is recorded on the VTR only when the image change occurs. 
     Many limitations are, however, imposed on the use of the method of detecting a change area on the basis of a difference between a background image and a current image. For example, a background image having no moving object must be prepared. 
     According to the method of detecting a change area on the basis of a difference between frames adjacent to each other along the time base, when an image change is moderate, the difference is small. In this case, therefore, it is difficult to detect a change area. 
     Furthermore, in the method of detecting a change area on the basis of a difference between images, erroneous detection of a change area tends to occur because of flickering of the light source or mixing of noise in a photoelectric scanning unit or an electronic circuit unit, and the like. 
     SUMMARY OF THE INVENTION 
     The present invention has been made in consideration of the above situation, and has as its object to easily and reliably detect an image change at a sufficiently high processing speed without using any dedicated device. 
     In order to achieve the above object, according to an aspect of the present invention, there is provided an image processing apparatus (method) including input means (step) for inputting a continuous image signal, detection means (step) for detecting a frame change in an image by comparing the image signal input by the input means (step) with a reference image signal, and storage means (step) for updating/storing the image signal input by the input means (step) as the reference image signal in units of frames in accordance with an output from the detection means (step). 
     It is another object of the present invention to accurately detect an image change without being affected by change areas (erroneously detected small areas dispersing randomly, in particular) erroneously detected because of flickering of a light source or mixing of noise in a photoelectric scanning unit, an electronic circuit unit, or the like. 
     In order to achieve the above object, according to another aspect of the present invention, there is provided an image processing apparatus (method) including input means (step) for inputting a continuous image signal, change component extraction means (step) for extracting change components between images by comparing the image signal input by the input means (step) with a reference image signal, erroneous extraction correction means (step) for detecting and removing an erroneously extracted change component from the change components extracted by the change component extraction means (step), and image change discrimination means (step) for discriminating an image change in the image signal on the basis of the change component corrected by the erroneous extraction correction means (step). 
     Other objects, features and advantages of the invention will become apparent form the following detailed description taken in conjunction with the accompanying drawings. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     FIG. 1 is a flow chart showing the contents of an image processing method according to the first to fourth embodiments of the present invention; 
     FIG. 2 is a block diagram showing an example of the arrangement of a motion image processing apparatus for performing the processing in FIG. 1; 
     FIG. 3 is a block diagram showing an example of the actual hardware arrangement for realizing the functions in FIG. 2; 
     FIG. 4 is a block diagram showing another example of the arrangement of the motion image processing apparatus for performing the processing in FIG. 1; 
     FIG. 5 is a view for explaining a pixel processing order in detecting an image change in the first and second embodiments; 
     FIG. 6 is a flow chart showing the processing in the image change detection step in the first embodiment; 
     FIG. 7 is a flow chart showing the processing in the image change detection step in the second embodiment; 
     FIG. 8 is a flow chart showing the processing in the image change detection step in the third embodiment; 
     FIGS. 9A and 9B are views for explaining an example of how an image is divided into blocks, a pixel processing order, and a block processing order in the third and fourth embodiments; 
     FIG. 10 is a flow chart showing another example of the processing in the image change detection step in the third embodiment; 
     FIG. 11 is a flow chart showing the processing in the image change detection step in the fourth embodiment; 
     FIG. 12 is a flow chart showing another example of the processing in the image change detection step in the fourth embodiment; 
     FIG. 13 is a flow chart showing the contents of an image processing method according to the fifth embodiment of the present invention; 
     FIG. 14 is a block diagram showing an example of the arrangement of a motion image processing apparatus for performing the processing in FIG. 13; 
     FIG. 15 is a block diagram showing another example of the arrangement of the motion image processing apparatus for performing the processing in FIG. 13; 
     FIG. 16 is a view showing an outline of a motion image processing method to which the present invention is applied; 
     FIG. 17 is a flow chart showing the contents of an image processing method according to the sixth to eighth embodiments of the present invention; 
     FIG. 18 is a block diagram showing an example of the arrangement of a motion image processing apparatus for performing the processing in FIG. 17; 
     FIG. 19 is a block diagram showing another example of the arrangement of a motion image processing apparatus for performing the processing in FIG. 17; 
     FIG. 20 is a view for explaining a pixel processing order in detecting an image change in the sixth to ninth embodiments; 
     FIG. 21 is a flow chart showing the detailed processing in the change component extraction step, the erroneous extraction correction step, and the image change discrimination step in the sixth embodiment; 
     FIG. 22 is a flow chart showing the detailed initialization processing in step S 501  in FIG. 21; 
     FIG. 23 is a flow chart showing the detailed processing in the change component extraction step, the erroneous extraction correction step, and the image change discrimination step in the seventh embodiment; 
     FIG. 24 is a flow chart showing the contents of an image processing method according to the eighth embodiment; 
     FIG. 25 is a block diagram showing an example of the arrangement of a motion image processing apparatus for performing the processing in FIG. 24; and 
     FIG. 26 is a block diagram showing another example of the arrangement of the motion image processing apparatus for performing the processing in FIG.  24 . 
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     An embodiment of the present invention will be described below with reference to the accompanying drawings. 
     FIG. 1 is a flow chart showing the contents of a motion image processing method according to the first embodiment. 
     Referring to FIG. 1, in image input step  1 , a still image is extracted from an image obtained by performing a photographing operation with a video camera or the like (not shown), a digital motion image stored in a disk unit (not shown), or the like, and the extracted image is input (this input still image will be referred to as an input image hereinafter). 
     In change detection step  2 , the input image input in image input step  1  and an image (to be referred to as a newest change image hereinafter) obtained when the newest change of several image changes caused in the past are compared with each other to detect a current image change. When an image change is detected, the flow advances to newest change image storage step  3 . If no image change is detected, the flow returns to image input step  1 . 
     In newest change image storage step  3 , the input image as an object to be compared when the image change is detected in change detection step  2  is stored as a newest change image. In image output step  4 , the input image obtained when the image change is detected in change detection step  2  is output to a communication path (not shown) (e.g., a WAN or LAN) to transmit it. Alternatively, the input image is output to an image storage device (not shown) to be stored, or is output to an image display device (not shown) to be displayed. 
     When the processing in image output step  4  is completed, the flow returns to image input step  1  again to repeatedly execute the above processing unless the end of the processing is designated. 
     FIG. 2 is a block diagram showing an example of the arrangement of an image processing apparatus for performing the processing in FIG.  1 . FIG. 3 shows an example of the arrangement of hardware for realizing the functions in FIG.  2 . 
     Referring to FIG. 3, a CPU (Central Processing Unit)  21  controls the overall operation of the motion image processing apparatus of this embodiment. A ROM (Read-Only Memory)  22  stores various processing programs. A RAM (Random Access Memory)  23  stores various kinds of information during processing. 
     A disk unit  24  stores information such as digital motion image information. A disk input/output device (disk I/O)  25  inputs/outputs digital motion image information stored in the disk unit  24 . A video camera  26  acquires image information by photographing an object to be photographed. A video capture device  27  captures a still image from an image obtained by the video camera  26 . 
     A communication device  28  transmits a still image input from the disk unit  24  via the disk I/O  25 , or transmits a still image, input from the video camera  26  via the video capture device  27 , via a communication path such as a WAN or LAN. The CPU  21 , the ROM  22 , the RAM  23 , the disk I/O  25 , the video capture device  27 , and the communication device  28  are connected to a bus  29 . 
     Referring to FIG. 2, an image input unit  11  acquires a still image from an image obtained by the video camera, a digital motion image stored in the disk unit, or the like. An input image storage unit  14  stores the still image. 
     Referring to FIG. 3, for example, the image input unit  11  may be constituted by a known image input unit which causes the video capture device  27  to acquire a still image (input image) from an image, obtained by performing a photographing operation with the video camera  26 , and stores the still image in the RAM  23  under the control of the CPU  21  which operates in accordance with programs stored in the ROM  22  or the RAM  23 . 
     Alternatively, the image input unit  11  may be constituted by a known image input unit which reads, via the disk I/O  25 , a still image (input image) from a digital motion image stored in the disk unit  24 , and stores the read image in the RAM  23  under the control of the CPU  21  which operates in accordance with programs stored in the ROM  22  or the RAM  23 . 
     Although not shown in FIG. 3, the image input unit  11  may be constituted by a known image input unit which causes a digital still camera to photograph a still image, and stores the image in the RAM  23  under the control of the CPU  21  which operates in accordance with programs stored in the ROM  22  or the RAM  23 . As is apparent, the image input unit  11  may be constituted by a combination of the above plurality of image input units. 
     A change detection unit  12  compares an input image stored in the input image storage unit  14  with an newest change image stored in a newest change image storage unit  15  to detect a current image change. When an image change is detected, the input image stored in the input image storage unit  14  is stored as a newest change image in the newest change image storage unit  15 . 
     For example, as shown in FIG. 3, the change detection unit  12  can be constituted by the CPU  21  which operates in accordance with programs stored in the ROM  22  or the RAM  23 , and the RAM  23  used as a work memory or the disk unit  24 . As is apparent, the change detection unit  12  may be constituted by a dedicated CPU, a dedicated RAM, and a dedicated disk unit, or dedicated hardware. 
     An image output unit  13  outputs and transmits, to a communication path (a WAN or LAN), an input image which is stored in the input image storage unit  14  when the change detection unit  12  detects an image change, outputs and stores the image in the image storage device, or outputs the image to the image display device to display it. 
     For example, referring to FIG. 3, the image output unit  13  can be constituted by a known image output unit which transmits an image to a communication path such as a WAN or LAN via the communication device  28  under the control of the CPU  21  which operates in accordance with programs stored in the ROM  22  or the RAM  23 . 
     Alternatively, the image output unit  13  my be constituted by a known image output unit which stores part of a digital motion image in the disk unit  24  under the control of the CPU  21  which operates in accordance with programs stored in the ROM  22  or the RAM  23 . In this case, the disk unit  24  may be a unit which can be used via a network such as a LAN. 
     Although not shown in FIG. 3, the image output unit  13  may be constituted by a known image output unit which continuously displays still images on the same portion on a display to display a motion image. As is apparent, the image output unit  13  may be constituted by a combination of the above plurality of image output units. 
     For example, referring to FIG. 3, the input image storage unit  14  and the newest change image storage unit  15  may be constituted by the RAM  23  or the disk unit  24 . As is apparent, each unit may be constituted by a dedicated storage device. 
     Note that the input image storage unit  14  and the newest change image storage unit  15  may be constituted by two image storage units  16   a  and  16   b  which are selectively used upon a switching operation, as shown in FIG.  4 . In this arrangement, every time an image change is detected by the change detection unit  12 , the roles of the image storage units  16   a  and  16   b  are switched in newest change image storage step  3  in FIG.  1 . 
     Assume that an image change is detected at a certain time point in the process of sequentially storing an input image in the image storage unit  16   a . In this case, the image storage unit  16   a  is switched to serve as a storage unit for storing a newest change image, whereas the image storage unit  16   b  is switched to serve as a storage unit for storing an input image. 
     With this operation, the input image stored in the image storage unit  16   a  when the image change is detected is used as a newest change image afterward, and the processing of copying an input image from the input image storage unit  14  to the newest change image storage unit  15  in the case shown in FIG. 2 can be omitted. 
     Note that the image storage units  16   a  and  16   b  need not be used as separate memories, but the above function can be realized by one memory with a bank switching operation. 
     The processing contents in each step in FIG. 1 will be described in detail with reference to the arrangements of FIGS. 2 and 3. 
     In image input step  1 , the image input unit  11  acquires a still image from an image obtained by the video camera  26  or a digital motion image stored in the disk unit  24 . Alternatively, the image input unit  11  photographs a still image using a digital still camera (not shown), and stores the still image in the input image storage unit  14 . 
     In change detection step  2 , the input image stored in the input image storage unit  14  is compared with the newest change image stored in the newest change image storage unit  15  to detect a current image change. 
     FIG. 5 shows an example of the contents of processing executed by the CPU  21  in accordance with programs stored in the ROM  22  or the RAM  23  in FIG. 3 in change detection step  2 . In this processing, the pixel value difference (absolute value) between each pair of corresponding pixels is calculated using an input image and a newest change image. If the total pixel value difference of the entire image is equal to or larger than a given value, it is determined that the input image changes from the newest change image. That is, it is determined that an image change has occurred. 
     In this case, pixel value differences are calculated by processing the respective pixels of an image in the raster scan order, as shown in FIG.  5 . The total pixel value difference during processing will be referred to as a total change amount. As is apparent, pixels may be processing concurrently. 
     Referring to FIG. 6, in step S 101 , the total change amount is initialized to 0. In step S 102 , the pixel value between currently processed pixels (to be referred to as subject pixels hereinafter) is calculated. 
     Assume that an input image is a binary image. In this case, the value of a pixel value difference is “1” if subject pixels have difference values, and is “0” if the subject pixels have the same value. If an input image is a halftone image, the value of a pixel value difference is the absolute value of the difference between subject pixel values. If an input image is a color image, the value of a pixel value difference is a value obtained by calculating the absolute values of the differences between R, G, and B values of subject pixels, and calculating the sum of the absolute values of the differences. 
     In step S 103 , the pixel value difference calculated in step S 102  is added to the total change amount. In step S 104 , it is checked whether the total change amount calculated in step S 103  is larger than a predetermined value (threshold value). If YES in step S 104 , it is determined that an image change has occurred, and the processing shown in FIG. 6 is terminated. If NO in step S 104 , the flow advances to step S 105 . 
     In step S 105 , it is checked whether all pixels have been processed. If YES in step S 105 , it is determined that no image change has occurred, and the processing in FIG. 6 is terminated. If NO in step S 105 , the flow advances to step S 106 . In step S 106 , processing is shifted to the next pixel (the next pixel is set as a subject pixel), and the flow return to step S 102 . 
     In newest change image storage step  3 , when an image change is detected in change detection step  2 , the input image stored in the input image storage unit  14  in image input step  1  is stored as a newest change image in the newest change image storage unit  15 . 
     In image output step  4 , when an image change is detected in change detection step  2 , the input image stored in the input image storage unit  14  is output and transmitted to a communication path (a WAN or LAN) via the communication device  28  or the like, output to the disk unit  24  or the like to be stored, or output to an image display device (not shown) to be displayed. 
     As described above, according to the first embodiment, an image which undergoes no change, e.g., a background image, need not be prepared as the above comparative image, and even a moderate image change can be reliably detected. 
     An image change can therefore be easily and reliably detected at a sufficiently high speed without any dedicated device. In addition, only when an image change is detected, the corresponding image data is output. With this operation, the image data amount can be reduced in outputting the image data. For example, only an image corresponding to a detected change is output to a communication path, a storage unit, or a display device to reduce the transmission, storage, or display data amount. 
     FIG. 16 shows an outline of the motion image processing method of the present invention. 
     The second embodiment of the present invention will be described next. 
     The second embodiment is another embodiment of the processing in change detection step  2  in the first embodiment. 
     FIG. 7 shows an example of the contents of processing executed by the CPU  21  in change detection step  2  in this embodiment in accordance with programs stored in the ROM  22  or the RAM  23  in FIG.  3 . 
     In this processing, the pixel value difference (absolute value) between each pair of corresponding pixels is calculated using an input image and a newest change image. If the value of each pixel value difference is equal to or larger than a given value (first threshold value), it is determined that the subject pixel has changed (a pixel having undergone a change will be referred to as a change pixel hereinafter). If the number of change pixels of the entire input image is equal to or larger than a given value (second threshold value), it is determined that the input image has changed as compared with the newest change image. That is, it is determined that an image change has occurred. 
     Similar to the first embodiment, as shown in FIG. 5, the above determination of a change pixel is performed by processing the respective pixels of an image in the raster scan order. Note that the total number of change pixels during processing will be referred to as the number of change pixels. As is apparent, pixels may be processed concurrently. 
     Referring to FIG. 7, in step S 201 , the number of change pixels is initialized. In step S 202 , the pixel value difference between subject pixels which are currently processed is calculated by the same method as in the first embodiment. 
     In step S 203 , it is checked whether the pixel value difference calculated in step S 202  is larger than a predetermined value (first threshold value). If YES in step S 202 , it is determined that a subject pixel has undergone a change, and the flow advances to step S 204  to increase the number of change pixels by one. If NO in step S 202 , it is determined that the subject pixel has undergone no change, and the flow jumps to step S 206 . 
     In step S 205  after step S 204 , it is checked whether the number of change pixels calculated in step S 204  is larger than a predetermined value (second threshold value). If YES in step S 205 , it is determined hat an image change has occurred, and the processing in FIG. 7 is terminated. If NO in step S 205 , the flow advances to step S 206 . 
     In step S 206 , it is checked whether all pixels have been processed. If YES in step S 206 , it is determined that no image change has occurred, and the processing in FIG. 7 is terminated. IF NO in step S 206 , the flow advances to step S 207 . In step S 207 , processing is shifted to the next pixel (the next pixel is set as a subject pixel), and the flow returns to step S 202 . 
     Similar to the first embodiment, in the second embodiment, an image change can be easily and reliably detected at a sufficiently high speed even without any dedicated device. In addition, only when an image change is detected, the corresponding image data is output to a communication path, a storage unit, or a display device. With this operation, the transmission, storage, or display data amount can be reduced. 
     The third embodiment of the present invention will be described next. 
     The third embodiment is still another embodiment of the processing in change detection step  2  in the first embodiment described above. 
     FIG. 8 shows an example of the contents of processing executed by the CPU  21  in accordance with programs stored in the ROM  22  or the RAM  23  in FIG. 3 in change detection step  2  in this embodiment. 
     In this processing, as shown in FIGS. 9A and 9B, an input image and a newest change image are divided into a plurality of blocks, and an image change is detected in units of blocks. Similar to the first embodiment, the pixel value difference between each pair of corresponding pixels is calculated using the input image and the newest change image. If the total pixel value difference in each block is larger than a given value (first threshold value), it is determined that an image change has occurred in the corresponding block. 
     If the number of blocks having undergone changes (to be referred to as change blocks hereinafter) of the entire input image is larger than a given value (second threshold value), it is determined that the input image has changed as compared with the newest change image. That is, it is determined that an image change has occurred. 
     Assume that pixel value differences in each block are calculated by processing the respective pixels in the raster scan order, as shown in FIG.  9 A. Assume also that the respective blocks are processed in the raster scan order, as shown in FIG.  9 B. Note that the total pixel value difference in a block which is being processed will be referred to as a total change amount; and the total number of change blocks, the number of change blocks. As is apparent, pixels or blocks may be processed concurrently. 
     Referring to FIG. 8, in step S 301 , the number of change blocks is initialized to 0. In step S 302 , the total change amount is initialized to 0. In step S 303 , the pixel value difference between subject pixels is calculated by the same method as that in the first embodiment. In step S 304 , the pixel value difference calculated in step S 303  is added to the total change amount. 
     In step S 305 , it is checked whether the total change amount calculated in step S 304  is larger than a predetermined value (first threshold value). If YES in step S 305 , it is determined that a change has occurred in the subject block, and the flow advances to step S 307  to add one to the number of change blocks. If NO in step S 305 , the flow advances to step S 306 . 
     In step S 306 , it is checked whether all the pixels in a subject block have been processed. If YES in step S 306 , it is determined that no change has occurred in the subject block, the flow advances to step S 311  to shift processing to the next block (the next block is set as a subject block), and the flow returns to step S 302 . If NO in step S 306 , the flow advances to step S 310  to shift processing to the next pixel (the next pixel is set as a subject pixel), and the flow returns to step S 303 . 
     In step S 308  following step S 307 , it is checked whether the number of change blocks calculated in step S 307  is larger than a predetermined value (second threshold value). If YES step S 308 , it is determined that an image change has occurred, and the processing in FIG. 8 is terminated. If NO in step S 308 , the flow advances to step S 309 . 
     In step S 309 , it is checked whether all blocks have been processed. If YES in step S 309 , it is determined that no image change has occurred, and the processing in FIG. 8 is terminated. If NO in step S 309 , the flow advances to step S 311  to shift processing to the next block, and the flow returns to step S 302 . 
     Note that the purpose of this processing is to detect the presence/absence of an image change. For this reason, when the number of change blocks exceeds the second threshold value, the processing is terminated. However, as shown in the flow chart of FIG. 10, processing may be continued up to the last block. 
     With this operation, although the processing amount increases, all change blocks in an entire image can be detected. By transmitting, storing, or displaying only the change blocks, the transmission, storage, or display data amount can be reduced. 
     The fourth embodiment of the present invention will be described next. 
     The fourth embodiment is still another embodiment of the processing in change detection step  2  in the first embodiment described above. 
     FIG. 11 shows an example of the contents of processing executed by the CPU  21  in accordance with programs stored in the ROM  22  or the RAM  23  in FIG. 3 in change detection step  2  in this embodiment. 
     In this processing, as shown in FIGS. 9A and 9B, an input image and a newest change image are divided into a plurality of blocks, and an image change is detected in units of blocks. Similar to the second embodiment, the pixel value difference between each pair of corresponding pixels is calculated using the input image and the newest change image. If the value of each pixel value difference is larger than a given value (first threshold value), it is determined that the subject pixels have undergone a change. 
     If the number of change pixels in each block is larger than a given value (second threshold value), it is determined that the corresponding block has undergone a change. If the number of change blocks in the entire input image is larger than a given value (third threshold value), it is determined that the input image has changed as compared with the newest change image. That is, it is determined that an image change has occurred. 
     Similar to the third embodiment, pixel value differences in each block are calculated by processing the respective pixels in the raster scan order, as shown in FIG. 9A, and the respective blocks are also processed in the raster scan order, as shown in FIG.  9 B. Note that the total number of change pixels in a block which is being processed will be referred to as the number of change pixels; and the total number of change blocks, the number of change blocks. As is apparent, pixels or blocks may be processed concurrently. 
     Referring to FIG. 11, in step S 401 , the number of change blocks is initialized to 0. In step S 402 , the number of change pixels is initialized to 0. In step S 403 , the pixel value difference between subject pixels is calculated by the same method as that in the first embodiment. 
     In step S 404 , it is checked whether the pixel value difference calculated in step S 403  is larger than a predetermined value (first threshold value). If YES in step S 404 , it is determined that the subject pixels have undergone a change, and the flow advances to step S 405  to add one to the number of change pixels. If NO in step S 404 , it is determined that the subject pixels have undergone no change, and the flow jumps to step S 407 . 
     In step S 406  following step S 405 , it is checked whether the number of change pixels calculated in step S 405  is larger than a predetermined value (second threshold value). If YES in step S 406 , it is determined that the subject block has undergone a change, and the flow jumps to step S 408  to add one to the number of change blocks. If NO in step S 406 , the flow advances to step S 407 . 
     In step S 407 , it is checked whether all the pixels in the subject block have been processed. If YES in step S 407 , it is determined that the subject block has undergone no change, and the flow advances to step S 412  to shift processing to the next block (the next block is set to be a subject block), and the flow returns to step S 402 . If NO in step S 407 , the flow advances to step S 411  to shift processing to the next pixel (the next pixel is set to be a subject pixel), and the flow returns to step S 403 . 
     In step S 409  following step S 408 , it is checked whether the number of change blocks calculated in step S 408  is larger than a predetermined value (third threshold value). If YES in step S 409 , it is determined that an image change has occurred, and the processing in FIG. 11 is terminated. If NO in step S 409 , the flow advances to step S 410 . 
     In step S 410 , it is checked whether all blocks have been processed. If YES in step S 410 , it is determined that no image change has occurred, and the processing in FIG. 11 is terminated. If NO in step S 410 , the flow advances to step S 412  to shift processing to the next block, and the flow returns to step S 402 . 
     Note that the purpose of this processing is to detect the presence/absence of an image change, as in the third embodiment. For this reason, when the number of change blocks exceeds the third threshold value, the processing is terminated. However, as shown in the flow chart of FIG. 12, the processing can be continued up to the last block. By transmitting, storing, or displaying only detected change blocks, the transmission, storage, or display data amount can be reduced as in the third embodiment. 
     The fifth embodiment of the present invention will be described next. 
     In the fifth embodiment, differential image forming step  5  is inserted between image input step  1  and change detection step  2  in the procedure in FIG. 1 in the first to fourth embodiments. 
     In differential image forming step  5 , differential processing using, e.g., a Sobel operator, is performed for an input image input in image input step  1  (an image having undergone differential processing will be referred to as a differential image hereinafter). Other processing steps  1  to  4  are performed in the same manner as in the first to fourth embodiments. However, in change detection step  2 , the same processing as that in the first to fourth embodiment is performed not for an input image but for a differential image. In addition, in newest change image storage step  3 , a differential image is stored instead of an input image. 
     With this operation, although the processing is complicated, the apparatus can be designed not to detect an image change due to a change in illumination. In some application of the present invention, it is preferable that an image change due to a change in illumination be not detected. A similar effect can be expected in the first to fourth embodiments as well depending on a method of setting threshold values. In this embodiment, however, there is no need to consider a change in illumination in setting a threshold value. 
     FIG. 14 is a block diagram showing an example of a motion image processing apparatus for performing the processing in FIG.  13 . Note that the arrangement shown in FIG. 14 can be realized by the hardware shown in FIG. 3, as in the first to fourth embodiments. 
     More specifically, a differential image forming unit  17  in FIG. 14 can be constituted by the CPU  21  which operates in accordance with programs stored in the ROM  22  or the RAM  23  in FIG. 3, and the RAM  23  used as a work memory or the disk unit  24 . The differential image forming unit  17  performs differential processing for an input image stored in an input image storage unit  14 , and stores the resultant differential image in a differential image storage unit  18 . For example, the differential image storage unit  18  can be constituted by the RAM  23  or the disk unit  24  in FIG.  3 . 
     The remaining means in FIG. 14 are the same as those in the first to fourth embodiments. However, a change detection unit  12  performs the same processing as that in the first to fourth embodiments with respect to a differential image stored in the differential image storage unit  18  instead of an input image stored in the input image storage unit  14 . A newest change image storage unit  15  does not store an input image stored in the input image storage unit  14  as a newest change image but stores a differential image stored in the differential image storage unit  18 . 
     The arrangement shown in FIG. 14 may be replaced with the arrangement shown in FIG. 15, as in the first to fourth embodiments. More specifically, the operation mode of the differential image storage unit  18  and the newest change image storage unit  15  in FIG. 14 can be changed such that two image storage units  16   a  and  16   b  are selectively used upon a switching operation, as shown in FIG.  15 . With this arrangement, the processing of copying a differential image from the differential image storage unit  18  to the newest change image storage unit  15 , which is performed in the case shown in FIG. 14, can be omitted. 
     FIG. 17 is a flow chart showing the contents of a motion image processing method according to the sixth embodiment of the present invention. 
     Referring to FIG. 17, in image input step  101 , a still image is extracted from an image obtained by performing a photographing operation with a video camera or the like (not shown), a digital motion image stored in a disk unit or the like (not shown), or the like, and the extracted image is input (this input still image will be referred to as an input image hereinafter). 
     In change component extraction step  102 , the input image input in image input step  1  and an image obtained upon detection of the newest change of several image changes in the past are compared with each other to detect and extract current image change components. 
     Image change components are extracted by using a newest change image for the following reason. Consider the above two conventional methods of detecting a change area on the basis of a difference between two images. In the method of detecting a change area on the basis of a difference between a background image photographed in advance and a current photographed image, for example, a background image having no moving object must be prepared. 
     In the method of detecting a change area on the basis of a difference between two frames adjacent to each other along the time axis, if an image change is moderate, the difference becomes small. It is therefore difficult to detect a change area. 
     In contrast to this, in the method of extracting change components by comparing an input image with a newest change image as in this embodiment, a changeless image such as a background image need not be prepared as a reference image to be compared with the input image, and even a small change in a moderate image change can be reliably detected and extracted. 
     In erroneous extraction correction step  103 , a component, of the change components extracted in change component extraction step  102 , which is considered as a component which has been erroneously extracted because of, e.g., flickering of a light source or mixing of noise in a photoelectric scanning unit, an electronic circuit unit, or the like is detected and corrected. 
     In image change discrimination step  104 , it is discriminated, on the basis of the change component corrected in erroneous extraction correction step  103 , whether an image change has occurred. If YES in step  104 , the flow advances to newest change image storage step  105 . If NO in step  104 , the flow returns to image input step  101 . 
     In newest change image storage step  105 , the input image from which the change components have been extracted in change component extraction step  102  is stored as a newest change image. In image output step  106 , the input image for which “CHANGE” is discriminated in image change discrimination step  104  is output to a communication path (e.g., a WAN or LAN) (not shown) to be transmitted, output to an image storage unit (not shown) to be stored, or output to an image display device to be displayed. 
     Upon completion of the processing in image output step  106 , the flow returns to image input step  101  to repeatedly execute the above processing, unless a processing end command is issued. 
     In the above processing, an image change can be detected with simple processing, i.e., differential processing. An image change can therefore be detected at a sufficiently high speed without any dedicated device for processing an image of a large data amount. In addition, since an image change is discriminated upon removal of an erroneously extracted component of an image change, an image change can be accurately detected. 
     By outputting an image only when an image change is detected, the corresponding image can be output after its data amount is reduced. For example, by outputting only an image for which an image change is detected to a communication path, a storage unit, or a display device, the transmission, storage, or display data amount can be reduced. 
     FIG. 18 is a block diagram showing an example of the arrangement of a motion image processing apparatus for performing the processing in FIG.  17 . 
     Note that a hardware arrangement for realizing the functions shown in FIG. 18 is the same as that shown in FIG.  3 . 
     Referring to FIG. 18, an image input unit  111  acquires a still image from an image obtained by a video camera, a digital motion image stored in a disk unit, or the like, and stores it in an input image storage unit  112 . 
     Referring to FIG. 3, for example, the image input unit  111  may be constituted by a known image input unit which causes the video capture device  27  to acquire a still image (input image) from an image, obtained by performing a photographing operation with the video camera  26 , and stores the still image in the RAM  23  under the control of the CPU  21  which operates in accordance with programs stored in the ROM  22  or the RAM  23 . 
     Alternatively, the image input unit  111  may be constituted by a known image input unit which reads, via the disk I/O  25 , a still image (input image) from a digital motion image stored in the disk I/O  25 , and stores the read image in the RAM  23  under the control of the CPU  21  which operates in accordance with programs stored in the ROM  22  or the RAM  23 . 
     Although not shown in FIG. 3, the image input unit  111  may be constituted by a known image input unit which causes a digital still camera to photograph a still image, and stores the image in the RAM  23  under the control of the CPU  21  which operates in accordance with programs stored in the ROM  22  or the RAM  23 . As is apparent, the image input unit  111  may be constituted by a combination of the above plurality of image input unit. 
     A change component extraction unit  113  compares an input image stored in the input image storage unit  112  with a newest change image stored in a newest change image storage unit  116  to extract current image change components. An erroneous extraction correction unit  114  detects and corrects a component, of the change components extracted by the change component extraction unit  113 , which is considered as a component which has been erroneously extracted because of, e.g., flickering of a light source or mixing of noise in a photoelectric scanning unit, an electronic circuit unit, or the like. 
     An image change discrimination unit  115  receives the image change components which has been corrected by the input image storage unit  14 , and discriminates whether an image change has occurred. If the unit  115  discriminates that an image change has occurred, a newest change image storage unit  116  reads out the corresponding input image stored in the input image storage unit  112 , and stores it as a newest change image. 
     Each of the change component extraction unit  113 , the erroneous extraction correction unit  114 , and the image change discrimination unit  115  can be constituted by the CPU  21  which operates in accordance with programs store din the ROM  22  or the RAM  23  in FIG. 3, and the RAM  23  used as a work memory or the disk unit  24 . As is apparent, each unit may be constituted by a dedicated CPU and a dedicated RAM or disk unit, or dedicated hardware. 
     If “CHANGE” is detected by the image change discrimination unit  115 , an image output unit  117  outputs the input image stored in the input image storage unit  112  to a communication path (e.g., a WAN or LAN) to transmit it, output to an image storage unit to store it, or output to an image display device to display it. 
     For example, referring to FIG. 3, the image output unit  117  can be constituted by a known image output unit which transmits an image to a communication path such as a WAN or LAN via the communication device  28  under the control of the CPU  21  which operates in accordance with programs stored in the ROM  22  or the RAM  23 . 
     Alternatively, the image output unit  117  my be constituted by a known image output unit which stores part of a digital motion image in the disk unit  24  under the control of the CPU  21  which operates in accordance with programs stored in the ROM  22  or the RAM  23 . In this case, the disk unit  24  may be a unit which can be used via a network such as a LAN. 
     Although not shown in FIG. 3, the image output unit  117  may be constituted by a known image output unit which continuously displays still images on the same portion on a display to display a motion image. As is apparent, the image output unit  117  may be constituted by a combination of the above plurality of image output units, and may be used by properly selecting the control programs for these units. 
     For example, referring to FIG. 3, the input image storage unit  112  and the newest change image storage unit  116  may be constituted by the RAM  23  or the disk unit  24 . As is apparent, each of the storage units  112  and  116  may be constituted by a dedicated storage device. 
     Note that the input image storage unit  112  and the newest change image storage unit  116  may be constituted by two image storage units  118   a  and  118   b  which are selectively used upon a switching operation, as shown in FIG.  19 . In this arrangement, every time an image change component is detected by the change component extraction unit  113 , the roles of the image storage units  118   a  and  118   b  are switched in newest change image storage step  106  in FIG.  17 . 
     Assume that an image change is detected at a certain time point in the process of sequentially storing an input image in the image storage unit  118   a . In this case, the image storage unit  118   a  is switched to serve as a storage unit for storing a newest change image, whereas the image storage unit  118   b  is switched to serve as a storage unit for storing an input image. 
     With this operation, the input image stored in the image storage unit  118   a  when the image change is detected is used as a newest change image afterward, and the processing of copying an input image from the input image storage unit  112  to the newest change image storage unit  116  in the case shown in FIG. 18 can be omitted. 
     Note that the image storage units  118   a  and  118   b  need not be used as separate memories, but the above function can be realized by one memory with a bank switching operation. 
     The processing contents in each step in FIG. 17 will be described in detail with reference to the arrangements of FIGS. 18 and 3. 
     In image input step  101 , the image input unit  111  acquires a still image from an image obtained by the video camera  26  or a digital motion image stored in the disk unit  24 . Alternatively, the image input unit  111  photographs a still image using a digital still camera (not shown), and stores the still image in the input image storage unit  112 . 
     In change component extraction step  102 , the input image stored in the input image storage unit  112  in the above manner is compared with the newest change image stored in the newest change image storage unit  116  to detect and extract current image change components. 
     The processing in change component extraction step  102  is performed by calculating the pixel value difference (absolute value) between each pair of corresponding pixels (pixels at identical positions in the respective images) using the input image and the newest change image, and by extracting a pixel value difference exceeding a given threshold value as an image change component. The following description will be made on the assumption that each pixel value difference is calculated by processing the respective pixels of an image in the raster scan order, as indicated by the arrow in FIG.  20 . As is apparent, however, pixels may be processed concurrently. 
     In erroneous extraction correction step  103 , a component, of the change components extracted by the change component extraction unit  113  in change component extraction step  102 , which is considered as a component which has been erroneously extracted because of, e.g., flickering of a light source or mixing of noise in a photoelectric scanning unit, an electronic circuit unit, or the like is detected and corrected, thereby generating corrected image change components. In addition, the sum total of corrected image change components is obtained. 
     In this erroneous extraction correction processing, first of all, it is checked whether a change component extracted in change component extraction step  102  satisfies the following two conditions: 
     (1) a condition in which the pixel value difference (absolute value) (corresponding to a subject pixel) between a given pair of corresponding pixels (pixels at identical positions in the respective images) of an input image and a newest change image is larger than a given value (threshold value 1), and all the pixel value differences (absolute values) (corresponding to eight pixels adjacent to the subject pixel (i.e., the currently processed pixel)) between pairs of corresponding pixels of the input image and the newest change image are equal to or smaller than the given value (threshold value 1); and 
     (2) a condition in which a pixel value difference (absolute value) (corresponding to a subject pixel) between a given pair of corresponding pixels of the input image and the newest change image is equal to or smaller than the given value (threshold value 1), and all the pixel value differences (absolute values) (corresponding to eight pixels adjacent to the subject pixel between pairs of corresponding pixels of the input image and the newest change image is larger than the given value (threshold value 1). 
     If condition (1) is satisfied, it is determined that an image change component is erroneously extracted. This value is not added to a total change amount (in this embodiment, the sum total of pixel value differences during processing (corrected image change components) will be referred to as a total change amount. A total change amount is calculated by processing the respective pixels in the raster scan order, as indicated by the arrow in FIG. 20, in the same manner as the above calculation of pixel value differences). 
     If condition (2) is satisfied, the pixel value difference (absolute value) between the corresponding pixels is changed to the mean value of pixel value differences (absolute values) at the positions of the surrounding eight pixels, and the mean value is added to the total change amount. If neither condition (1) nor condition (2) is satisfied, the pixel value difference (absolute value) between the corresponding pixels itself is added to the total change amount. 
     That is, corrected image change components are defined such that the pixel value difference (absolute value) between pixels corresponding to condition (1), of two conditions (1) and (2), is set to be 0, the pixel value difference (absolute value) between pixels corresponding to condition (2) is set to be the mean value of pixel value differences (absolute values) at the positions of eight pixels around a subject pixel, and a pixel value difference between pixels corresponding to neither condition (1) nor condition (2) is a pixel value difference (absolute value) extracted in change component extraction step  102 . 
     In image change discrimination step  104 , an image change is discriminated on the basis of the sum total (total change amount) of image change components corrected by the erroneous extraction correction unit  114  in erroneous extraction correction step  103 . More specifically, the above total change amount is compared with a predetermined value (threshold value 2). If the total change amount is larger than threshold value 2, it is discriminated that “THERE IS CHANGE”. If the total change amount is not larger than threshold value 2 after all the pixels in the frame are processed, it is discriminated that “THERE IS NO CHANGE” in the frame. 
     The flow chart of FIG. 21 shows an example of the contents of processing executed by the CPU  21  in change component extraction step  102 , erroneous extraction correction step  103 , and image change discrimination step  104  in FIG. 17 in accordance with programs stored in the ROM  22  or the RAM  23  in FIG.  3 . 
     In the processing shown in FIG. 21, the pixel value difference (absolute value) between each pair of corresponding pixels of an input image and a newest change image is calculated. Of the calculated pixel value differences, only pixel value differences each having a value exceeding a given value (threshold value 1) are added throughout the image. If the total value (total change amount) exceeds another given value (threshold value 2), it is discriminated that the input image has changed as compared with the newest change image, i.e., “THERE IS CHANGE”. If the total change amount of the entire image is equal to or smaller than threshold value 2, it is discriminated that “THERE IS NO CHANGE”. 
     Assume that the pixel value difference (absolute value) between a given pair of corresponding pixels exceeds threshold value 1, but all pixel value differences corresponding to eight pixels adjacent to the subject pixel having the above pixel value difference are equal to or smaller than threshold value 1. In this case, it is determined that the pixel value difference at the subject pixel position is an erroneously extracted component, i.e., a change component is erroneously extracted. Therefore, this value is not added to the total change amount. 
     Assume that the pixel value difference (absolute value) between a given pair of corresponding pixels is equal to or smaller than a given value (threshold value 1), but all pixel value differences corresponding to eight pixels adjacent to the subject pixel having the above pixel value difference are larger than threshold value 1. In this case, it is determined that extraction of an image change component has been omitted, and the pixel value difference at the subject pixel position is changed to the mean value of the respective pixel value differences (absolute values) at the surrounding eight pixel positions. This mean value is then added to the total change amount. 
     The processing in this embodiment will be described with reference to the flow chart of FIG.  21 . 
     Referring to FIG. 21, in step S 501 , initialization processing required for erroneous extraction correction processing using a nine-pixel area (3 pixels (vertical)×3 pixels (horizontal)) is performed. As described above, in order to determine erroneous extraction of an image change component, pixel value differences corresponding to eight pixels around a subject pixel position for determination of erroneous extraction must be obtained in advance. FIG. 20 shows this state. 
     Assume that a position A is a subject position for determination of erroneous extraction in FIG.  20 . In this case, a nine-pixel area (3 pixels (vertical)×3 pixels (horizontal)) indicated by the hatched portion includes pixel positions (to be referred to as a noise discrimination subject area hereinafter) as reference positions for discrimination of erroneous extraction concerning the subject position A. Referring to FIG. 20, processing is performed in the raster scan order. For this reason, in discriminating erroneous extraction concerning the subject position A, a pixel value difference (absolute value) at a pixel position B required for subsequent discrimination is calculated in advance. 
     The initialization processing in step S 501  will be described in detail with reference to the flow chart of FIG.  22 . 
     Referring to FIG. 22, in step S 1001 , a total change amount is set to zero. In step S 1002 , the difference in the number of pixels ((x+2) where x is the number of pixels in the main scanning direction) between the pixel value calculation position (position B in FIG. 20) and the subject position of noise discrimination (position A in FIG. 20) is set in a first temporary buffer (not shown). 
     In step S 1003 , the memory address of an output destination to which a pixel value difference calculation result is to be output and the memory address of an output destination to which a discrimination result indicating whether the calculated pixel value difference is larger than predetermined threshold value 1 is to be output are respectively set in second and third temporary buffers (not shown). In this case, the output destinations of the pixel value difference and the comparison result indicating whether the pixel value difference is larger than threshold value 1 are independently ensured in free areas in the RAM  23 . 
     In step S 1004 , a pixel position where a pixel value difference is to be calculated is set as the head pixel position (the head position of a frame) in the raster scan order in a fourth temporary buffer (not shown). In step S 1005 , a pixel value difference at the pixel position set in the fourth temporary buffer is calculated. This calculated pixel value difference is output to the pixel value difference output destination (a free area in the RAM  23 ) held in the second temporary buffer. 
     In this case, if the input image is a halftone image, the pixel value difference is, for example, the absolute value of the difference between subject pixels. If the input image is a color image, the pixel value difference is, for example, the sum of the absolute values of the differences between R, G, and B values of subject pixels. 
     In step S 1006 , it is checked whether the pixel value difference calculated in step S 1005  is larger than predetermined threshold value 1. If YES in step S 1006 , the flow advances to step S 1007 . If NO in step S 1006 , the flow advances to step S 1008 . 
     In step S 1007 , as a signal indicating that the pixel value difference at the subject pixel position is larger than predetermined threshold value 1, “1” (also called a black pixel) is output to a bit map data holding area (the output destination of the discrimination result indicating that the pixel value difference is larger than threshold value 1) corresponding to the subject pixel position set in the third temporary buffer. The flow then advances to step S 1009 . 
     In step S 1008 , as a signal indicating that the pixel value difference at the subject pixel position is equal to or smaller than predetermined threshold value 1, “0” (also called a white pixel) is output to a bit map data holding area corresponding to the subject pixel position. The flow then advances to step S 1009 . 
     In the RAM  23 , the above bit map data holding area is a bit map image data area having the same size as that of an image for which change detection is being performed. At each pixel position of the image for which change detection is being performed, binary image data (black or white pixel data) consisting of a corresponding pixel is to be held. 
     In step S 1009 , the pixel position set in the fourth temporary buffer is updated to shift the pixel position, at which a pixel value difference is to be calculated, by one pixel ahead. In step S 1010 , the contents set in the second temporary buffer are updated to shift the output destination of the pixel value difference calculation result by one pixel ahead. In addition, the contents set in the third temporary buffer are updated to shift, by one pixel ahead, the output destination to which the discrimination result indicating that the calculated pixel value difference is larger or smaller than predetermined threshold value 1 is to be output. 
     In step S 1011 , the value (the difference in the number of pixels between the pixel value difference calculation position and the subject position of noise discrimination) set in the first temporary buffer is decreased by one. In step S 1012 , it is checked whether the value set in the first temporary buffer is zero. With this operation, it is checked whether all the pixels required for initialization have been processed. 
     If it is discriminated that the value in the first temporary buffer is zero, it is determined that all the pixels required for initialization have been processed. The processing in step S 101  in FIG. 6 is then terminated, and the flow returns to the initial processing routine. If the value in the first temporary buffer is not zero, the flow returns to step S 1005  to further perform initialization processing. 
     In step S 502  in FIG. 21, a pixel value difference at the pixel position (subject position of noise discrimination) set in the fourth temporary buffer is calculated. The calculated pixel value difference is output to the pixel value difference output destination held in the second temporary buffer. In step S 503 , it is checked whether the pixel value difference calculated in step S 502  is larger than predetermined threshold value 1. If YES in step S 503 , the flow advances to step S 504 . If NO in step S 503 , the flow advances to step S 505 . 
     In step S 504 , as a signal indicating that the pixel value difference at the pixel value difference calculation position in step S 502  is larger than predetermined threshold value 1, data of “1” (black pixel) is output to a bit map data holding area corresponding to the subject pixel position set in the third temporary buffer. The flow then advances to step S 506 . 
     In step S 505 , as a signal indicating that the pixel value difference at the pixel value difference calculation position in step S 502  is equal to or smaller than predetermined threshold value 1, data of “0” (white pixel) is output to a bit map data holding area corresponding to the subject pixel position. The flow then advances to step S 506 . 
     In step S 506 , whether the pixel value difference (absolute value) at a subject position of noise discrimination (e.g., the position A in FIG. 20) satisfies condition (1) described above is discriminated. More specifically, whether the pixel value difference at the subject position A exceeds threshold value 1, and the pixel value difference at each of eight pixel positions adjacent to the pixel position A is equal to or smaller than threshold value 1 is discriminated in the following manner. 
     The binary image data stored in the bit map data holding area corresponding to the nine-pixel area (3 pixels (vertical)×3 pixels (horizontal)) (the noise discrimination subject area indicated by hatching in FIG. 20) around the subject position A of noise discrimination are referred to check whether the central pixel of the noise discrimination subject area is a black isolated point (only the central pixel is a black pixel, but all the surrounding eight pixels are white pixels). With this operation, the above discrimination processing is performed. If it is discriminated that the central pixel is a black isolated point, the flow advances to step S 513 . Otherwise, the flow advances to step S 507 . 
     In step S 507 , whether the pixel value difference (absolute value) at a subject position of noise discrimination (e.g., the position A in FIG. 20) satisfies condition (2) described above is discriminated. More specifically, whether the pixel value difference at the subject position A is equal to or smaller than threshold value 1, and the pixel value difference at each of eight pixel positions adjacent to the pixel position A is larger than threshold value 1 is discriminated in the following manner. 
     The binary image data stored in the bit map data holding area corresponding to the nine-pixel area (3 pixels (vertical)×3 pixels (horizontal)) (the noise discrimination subject area indicated by hatching in FIG. 20) centered on the subject position A of noise discrimination are referred to check whether the central pixel of the noise discrimination subject area is a white isolated point (only the central pixel is a white pixel, but all the surrounding eight pixels are black pixels). With this operation, the above discrimination processing is performed. If it is discriminated that the central pixel is a white isolated point, the flow advances to step S 508 . Otherwise, the flow advances to step S 509 . 
     In step S 508 , the mean value of the pixel value differences (absolute values) at the eight pixel positions around the subject position A in the nine-pixel area (3 pixels (vertical)×3 pixels (horizontal)) (the noise discrimination subject area indicated by hatching in FIG. 20) centered on the subject position A of noise discrimination is calculated by referring to the area of the RAM  23  in which the pixel value difference calculation result is held. The obtained mean value is then set as the pixel value difference at the subject position A of noise discrimination. 
     In step S 509 , whether the pixel value difference (absolute value) at the subject position A of noise discrimination is larger than threshold value 1 is discriminated by referring to the binary image data stored in the bit map data holding area corresponding to the subject position A of noise discrimination and checking whether the pixel at the subject position A of noise discrimination is a black pixel. If a black pixel is discriminated in step S 509 , the flow advances to step S 510 . Otherwise, the flow advances to step S 513 . 
     In step S 510 , the pixel value difference (the above mean value after the processing in step S 508 ; the value calculated in step S 502  after the processing in step S 509 ) is added to the total change amount to obtain a new total change amount. In step S 511 , it is checked whether the total change amount updated in step S 510  is larger than predetermined threshold value 2. If YES in step S 511 , the flow advances to step S 512 . If NO in step S 511 , the flow advances to step S 513 . 
     In step S 512 , it is discriminated that an image change has occurred, and the processing in the flow chart of FIG. 21 is terminated. In step S 513 , it is checked whether all pixels have been processed. If YES in step S 513 , the flow advances to step S 514  to discriminate that no image change has occurred, and the processing in the flow chart of FIG. 21 is terminated. If NO in step S 513 , the flow advances to step S 515 . 
     In step S 515 , processing is shifted to the next pixel. That is, both the pixel value difference calculation position and the subject position of noise discrimination are shifted to the next pixels to set a new subject pixel for noise discrimination. The flow then returns to step S 502 . 
     In the above processing, a nine-pixel area (3 pixels (vertical)×3 pixels (horizontal)) centered on a subject position of noised discrimination may include a portion where no corresponding binary image data or no pixel value difference exists, as in a case wherein the above subject position is at an end portion (upper, lower, left, or right end) of the image. In this case, such a portion is handled as white pixel data or “0”. 
     If it is discriminated in image change discrimination step  104  that an image change has occurred, the input image input in image input step  101  and stored in the input image storage unit  112  is stored as a newest change image in the newest change image storage unit  116  in newest change image storage step  105 . 
     If it is discriminated in image change discrimination step  104  that an image change has occurred, the input image stored in the input image storage unit  112  is output to a communication path (a WAN or LAN) via the communication device  28  or the like to be transmitted, output to the disk unit  24  to be stored, or output to an image display device (not shown) to be displayed in image output step  106 . 
     As described above, according to the sixth embodiment, fine change components dispersing randomly are extracted and removed, as erroneously extracted image change components, from change components extracted by comparison between a subject image whose motion is to be detected and a newest change image. On the basis of the change components corrected in this manner, it can be determined whether the above image has undergone a change. Therefore, an image change can be detected without being affected by, e.g., change components produced randomly in the image because of flickering of a light source or mixing of noise in a photoelectric scanning unit, an electronic circuit unit, or the like. That is, an image change can be accurately detected. 
     The seventh embodiment of the present invention will be described next. 
     The seventh embodiment is another embodiment of the processing in change component extraction step  102 , erroneous extraction correction step  103 , and image change discrimination step  104  in the sixth embodiment. 
     FIG. 23 is a flow chart showing an example of the contents of processing executed by the CPU  21  in change component extraction step  102 , erroneous extraction correction step  103 , and image change discrimination step  104  in the seventh embodiment in accordance with programs stored in the ROM  22  or the RAM  23  in FIG.  3 . 
     In the processing shown in FIG. 23, the pixel value difference (absolute value) between each pair of corresponding pixels is calculated using an input image and a newest change image. If each pixel value difference is larger than a given value (threshold value 1), it is determined that the corresponding subject pixel has undergone a change (a pixel having undergone a change will be referred to as a change pixel hereinafter). If the number of change pixels in the entire input image is larger than a given value (threshold value 3), it is determined that the input image has changed as compared with the newest change image. That is, it is determined that an image change has occurred. 
     Assume that the pixel value difference (absolute value) between a given pair of corresponding pixels is larger than threshold value 1, but all pixel value differences corresponding to eight pixels adjacent to the subject pixel having the above pixel value difference are equal to or smaller than threshold value 1. In this case, it is determined that the pixel value difference at the subject pixel position is an erroneously extracted component, i.e., an erroneously extracted change component. Therefore, this subject pixel is not counted as a change pixel. 
     Assume that the pixel value difference (absolute value) between a given pair of corresponding pixels is equal to or smaller than threshold value 1, but all pixel value differences corresponding to eight pixels adjacent to the subject pixel having the above pixel value difference are larger than threshold value 1. In this case, it is determined that extraction of an image change component has been omitted, and this subject pixel is counted as a change pixel. 
     Similar to the sixth embodiment, the above change pixel discrimination processing is performed by processing the respective pixels in an image in the raster scan order, as shown in FIG. 20, and the sum total of change pixels during processing will be referred to as the number of change pixels. As is apparent, pixels may be processed concurrently. 
     The processing in this embodiment will be described below with reference to the flow chart of FIG.  23 . 
     Referring to FIG. 23, in step S 601 , initialization processing required for erroneous extraction correction processing using a nine-pixel area (3 pixels (vertical)×3 pixels (horizontal)) is performed as in the processing in step S 501  in FIG.  21 . 
     In step S 601 , processing is performed in the raster scan order, as shown in FIG.  20 . For this reason, in discriminating erroneous extraction concerning the subject position A, a pixel value difference (absolute value) at the pixel position B which is required for the subsequent discrimination processing is calculated, and it is discriminated in advance whether each calculated pixel value difference is larger than predetermined threshold value 1. 
     If it is discriminated that a given pixel value difference is larger than predetermined threshold value 1, a black pixel is assigned. Otherwise, a white pixel is assigned. With this operation, binary image data consisting of pixels corresponding to the respective pixel positions of the image for which change detection is being performed are generated in advance. 
     The initialization processing in step S 601  can be realized by executing the processing in the flow chart of FIG. 22, as in the initialization processing in step S 501  in FIG.  21 . 
     In the seventh embodiment, however, the second temporary buffer used in the sixth embodiment and the memory area for holding a pixel value difference itself are not required. For this reason, in the processing in steps S 1003 , S 1005 , and S 1010  in FIG. 22, processing associated with the second temporary buffer in the sixth embodiment and the memory area for holding a pixel value difference itself is not required. 
     In the seventh embodiment, “SET TOTAL CHANGE AMOUNT TO ZERO” in step S 1001  in FIG. 22 is replaced with “SET NUMBER OF CHANGE PIXELS TO ZERO”. 
     In step S 602  in FIG. 23, a pixel value difference at a pixel value difference calculation position (subject position of noise discrimination) is calculated by the same method as in the sixth embodiment. In step S 603 , it is checked whether the pixel value difference calculated in step S 602  is larger than predetermined threshold value 1. If YES in step S 603 , the flow advances to step S 604 . If NO in step S 603 , the flow advances to step S 605 . 
     In step S 604 , as a signal indicating that the pixel value difference at the pixel value difference calculation position in step S 602  is larger than predetermined threshold value 1, data of “1” (black pixel) is output to a bit map data holding area corresponding to the subject pixel position set in a third temporary buffer (not shown). The flow then advances to step S 606 . 
     In step S 605 , as a signal indicating that the pixel value difference at the pixel value difference calculation position in step S 602  is equal to or smaller than predetermined threshold value 1, data of “0” (white pixel) is output to a bit map data holding area corresponding to the subject pixel position. The flow then advances to step S 606 . 
     In step S 606 , similar to the sixth embodiment, whether the pixel value difference at the subject position of noise discrimination (e.g., the position A in FIG. 20) satisfies condition (1) described above is discriminated by checking whether the subject position A of noise discrimination is a black isolated point in the nine-pixel area (3 pixels (vertical)×3 pixels (horizontal)) (the noise discrimination subject area indicated by hatching in FIG. 20) centered on the subject position A. If the subject position A is a black isolated point, the flow advances to step S 612 . Otherwise, the flow advances to step S 607 . 
     In step S 607 , similar to the sixth embodiment, whether the pixel value difference at the subject position of noise discrimination (e.g., the position A in FIG. 20) satisfies condition (2) described above is discriminated by checking whether the subject position A of noise discrimination is a white isolated point in the nine-pixel area (3 pixels (vertical)×3 pixels (horizontal)) (the noise discrimination subject area indicated by hatching in FIG. 20) centered on the subject position A. If the subject position A is a white isolated point, the flow advances to step S 609 . Otherwise, the flow advances to step S 608 . 
     In step S 608 , whether the pixel value difference (absolute value) at the subject position A of noise discrimination is larger than threshold value 1 is discriminated by referring to the binary image data stored in the bit map data holding area corresponding to the subject position A of noise discrimination and checking whether the pixel at the subject position A of noise discrimination is a black pixel. If the subject position A is a black pixel, the flow advances to step S 609 . Otherwise, the flow advances to step S 612 . 
     In step S 609 , the number of change pixels is increased by one to set a new number of change pixels. In step S 610 , it is checked whether the number of change pixels updated in step S 609  is larger than predetermined threshold value 3. If YES in step S 610 , the flow advances to step S 611 . If NO in step S 610 , the flow advances to step S 612 . 
     In step S 611 , it is discriminated that an image change has occurred, and the processing in the flow chart of FIG. 23 is terminated. In step S 612 , it is checked whether all pixels have been processed. If YES in step S 612 , the flow advances to step S 613  to discriminate that no image change has occurred. The processing in the flow chart of FIG. 23 is then terminated. If NO in step S 612 , the flow advances to step S 614 . 
     In step S 614 , processing is shifted to the next pixel. That is, both the pixel value difference calculation position and the subject position of noise discrimination are shifted to the next pixels to set a new subject pixel for noise discrimination. The flow then returns to step S 602 . 
     In the above processing, a nine-pixel area (3 pixels (vertical)×3 pixels (horizontal)) centered on a subject position of noised discrimination may include a portion where no corresponding binary image data exists, as in a case wherein the above subject position is at an end portion (upper, lower, left, or right end) of the image. In this case, this area is handled as white pixel data. 
     In the seventh embodiment, similar to the sixth embodiment, an image change can be detected without being affected by, e.g., change components produced randomly in the image because of flickering of a light source or mixing of noise in a photoelectric scanning unit, an electronic circuit unit, or the like. That is, an image change can be accurately detected. 
     The eighth embodiment of the present invention will be described next. 
     In the sixth and seventh embodiments described above, as subject pixel positions, two positions, i.e., “the subject position of noise discrimination” and “the pixel value difference calculation position” like the positions A and B in FIG. 20 are set, and an appropriate difference ((the number of pixels of an image in the main scanning direction)+two pixels) is set between the two positions. An image change is detected by performing raster scanning once for every still image. However, the present invention is not limited to this. 
     For example, raster scanning may be performed twice for every still image. In the first scanning operation, pixel value differences in one entire image are calculated, and binary image data representing a discrimination result indicating whether each calculated pixel value difference exceeds predetermined threshold value 1 is formed. In the second scanning operator for the same still image, noise discrimination and discrimination of the image as a change image may be performed. 
     In addition, the difference to be set between the two subject pixel positions (the subject position of noise discrimination and the pixel value difference calculation position) is not limited to ((the number of pixels of an image in the main scanning direction)+two pixels). For example, a difference of ((the number of pixels of an image in the main scanning direction)×2+three pixels) may be set. 
     In this case, erroneous extraction discrimination can be performed by referring to a 25-pixel area (5 pixels (vertical)×5 pixels (horizontal)) centered on the subject position of noise discrimination. For example, it is discriminated that a change component is erroneously extracted, if the central pixel in the 25-pixel area is a white pixel, but all the surrounding 24 pixels are black pixels, or if 22 or more pixels of the surrounding 24 pixels have values different from the value of the central pixel. 
     The ninth embodiment of the present invention will be described next. 
     In the ninth embodiment, as shown in FIG. 24, differential image forming step  107  is inserted between image input step  101  and change component extraction step  102  in the procedure shown in FIG. 17 in the sixth to eighth embodiments. 
     In differential image forming step  107 , differential processing using, e.g., a Sobel operator, is performed for an input image input in image input step  101  (an image having undergone differential processing will be referred to as a differential image hereinafter). Other processing steps  101  to  106  are performed in the same manner as in the sixth to eighth embodiments. However, in change component extraction step  102 , the same processing as that in the sixth to eighth embodiment is performed not for an input image but for a differential image. In addition, in newest change image storage step  105 , a differential image is stored instead of an input image. 
     With this operation, although the processing is complicated, the apparatus can be designed not to detect an image change due to a change in illumination. In some application of the present invention, it is preferable that an image change due to a change in illumination be not detected. A similar effect can be expected in the sixth to ninth embodiments as well depending on a method of setting threshold values. In this embodiment, however, there is no need to consider a change in illumination in setting a threshold value. 
     FIG. 25 is a block diagram showing an example of a motion image processing apparatus for performing the processing in FIG.  24 . Note that the arrangement shown in FIG. 25 can be realized by the hardware shown in FIG. 3, as in the sixth to ninth embodiments. 
     More specifically, a differential image forming unit  119  in FIG. 25 can be constituted by the CPU  21  which operates in accordance with programs stored in the ROM  22  or the RAM  23  in FIG. 3, and the RAM  23  used as work memory or the disk unit  24 . The differential image forming unit  119  performs differential processing for an input image stored in an input image storage unit  112 , and stores the resultant differential image in a differential image storage unit  120 . 
     In addition, for example, the differential image storage unit  120  can be constituted by the RAM  23  or the disk unit  24  in FIG. 3, similar to the input image storage unit  112  and a newest change image storage unit  116  in FIG.  25 . As is apparent, the respective storage units  112 ,  116 , and  120  may be constituted by dedicated storage devices. 
     The remaining means in FIG. 25 are the same as those in the sixth to ninth embodiments. However, a change component extraction unit  113  performs the same processing as that in the sixth to ninth embodiments with respect to a differential image stored in the differential image storage unit  120  instead of an input image stored in the input image storage unit  112 . The newest change image storage unit  116  does not store an input image stored in the input image storage unit  112  as a newest change image but stores a differential image stored in the differential image storage unit  120 . 
     The arrangement shown in FIG. 25 may be replaced with the arrangement shown in FIG. 26, as in the sixth to ninth embodiments. More specifically, the operation mode of the differential image storage unit  120  and the newest change image storage unit  116  in FIG. 25 can be changed such that two image storage units  118   a  and  118   b  are selectively used upon a switching operation, as shown in FIG.  26 . With this arrangement, the processing of copying a differential image from the differential image storage unit  120  to the newest change image storage unit  116 , which is performed in the case shown in FIG. 25, can be omitted. 
     The first to ninth embodiments can be effectively applied to video conference systems and monitoring systems. 
     The present invention can be practiced in other various forms without departing from its spirit and scope. 
     In other words, the foregoing description of embodiments has been given for illustrative purposes only and not to be construed as imposing any limitation in every respect. 
     The scope of the invention is, therefore, to be determined solely by the following claims and not limited by the text of the specifications and alterations made within a scope equivalent to the scope of the claims fall within the true spirit and scope of the invention.