the preferred embodiments of an image processing apparatus according to the present invention will be described in detail hereinafter with reference to the accompanying drawings . fig1 is a block diagram showing the arrangement of an image search apparatus according to an embodiment of the present invention . the arrangement and operation of the image search apparatus will be explained below with reference to fig1 . an image database 1 stores a large number of images , which are input by an image input unit 8 and are encoded and compressed by an encoding unit 9 . an input unit 2 reads encoded data of a test image from the image database 1 and outputs it to a comparison unit 5 . on the other hand , information which is input from a shape input unit 3 as a query condition and pertains to the shape of an image , is processed by a shape information generation unit 4 , and is output to the comparison unit 5 . the comparison unit 5 compares the data input from the input unit 2 and shape information generation unit 4 . when the two data do not satisfy a predetermined condition , the comparison unit 5 sends a control signal that instructs to input encoded data of the next image to the input unit 2 . conversely , when the two data satisfy the predetermined condition , the comparison unit 5 sends a control signal that instructs to decode the corresponding encoded data in the image database 1 to a decoder 6 . the decoder 6 reads out the encoded data designated by the comparison unit 5 from the image database 1 , decodes it , and sends the decoded data to a display unit 7 . hence , the display unit 7 displays an image that matches the image shape which is input from the shape input unit 3 as a query condition . the arrangements and operations of the individual units will be described below . the image database 1 stores test images , and is a storage device using a storage medium such as a hard disk , magnetooptical disk , optical disk , or the like . individual images stored in the storage device are encoded and compressed , and the encoding procedure and the format of a bitstream generated will be explained below . fig2 is a schematic block diagram showing the arrangement of the encoding unit 9 . an image to be encoded undergoes the discrete wavelet transform by a discrete wavelet transformer e 1 , and is segmented into a series of coefficients which belong to a predetermined number of different frequency bands ( to be referred to as sub - bands hereinafter ). since the procedure of the discrete wavelet transform is known to those who are skilled in the art , a detailed description thereof will be omitted . fig3 shows sub - bands obtained by the discrete wavelet transform , and in this example , there are 10 sub - bands . coefficients which belong to these sub - bands are output in turn to a quantizing unit e 2 . the quantizing unit e 2 quantizes the coefficients of the input sub - bands by a predetermined quantizing step , and outputs quantizing indices to an entropy encoder e 3 in units of bit planes . in this embodiment , an identical quantizing step is used for the respective sub - bands , but may be changed in units of sub - bands . the entropy encoder e 3 outputs a bitstream obtained by encoding the input quantizing indices in units of bit planes . the bitstream obtained in this manner is stored in the image database 1 , and has a structure , as shown in fig4 a and 4b . fig4 a shows the format of the overall bitstream , in which header information including an image size , transformation level in the wavelet transform , and maximum and minimum bit plane numbers n max and n min , is followed by a bitstream that indicates actual transform coefficients . fig4 b shows the format of the bitstream , which consists of a sequence of bit information in units of sub - bands in the order from the maximum to minimum bit planes . a search method of images stored in the image database 1 in the bitstream format shown in fig4 a and 4b will be explained below . the shape input unit 3 shown in fig1 inputs an image shape as a query condition , and is constructed by an input device including some means that allows the operator to input a shape , e . g ., a pointing device such as a mouse , tablet or the like , and a display device such as a crt or lcd that allows the operator to visually confirm the input shape . the shape input method is not particularly limited as long as it is normally used in a computer . for example , a shape drawn on the screen may be modified to a desired one by mouse operation . alternatively , an image that expresses a desired shape may be scanned by an input device such as a scanner or the like . the input data indicating the image shape is output as , e . g ., a binary image to the shape information generation unit 4 . fig5 is a block diagram showing the arrangement of the shape information generation unit 4 . a resolution converter 401 converts input shape data into a predetermined size to match it with the resolution of data used in shape comparison . an edge detector 402 detects the edge of the input binary image , and outputs an edge image indicating the detection result . fig6 a and 6b are views for explaining the operation of the edge detector 402 . a shape image shown in fig6 a is converted into an edge image shown in fig6 b , and the converted edge image is output to the comparison unit 5 . note that black pixels that assume a value ‘ 1 ’ in the edge image of this embodiment indicate an edge , and other pixels are white pixels that assume a value ‘ 0 ’. on the other hand , images stored in the image database 1 are read out in turn by the input unit 2 . in this case , the bitstream to be read out has the structure shown in fig4 a and 4b . the input unit 2 reads out data of a predetermined level having the same resolution as that of the edge image from sub - bands other than sub - band ll in the bitstream corresponding to bit plane n max , and outputs them to the comparison unit 5 . the encoded data input to the comparison unit 5 are entropy - decoded to reconstruct coefficients or indices quantized upon encoding . fig7 is a schematic diagram showing the comparison procedure between the reconstructed sub - bands and edge image , which is implemented by the comparison unit 5 . input three sub - bands are ored to be synthesized into a single sub - band , and the difference between the synthesized sub - band and edge image is calculated . then , a test image or sub - band is segmented into blocks having a predetermined size , and when the sum of the absolute values of the differences in these blocks is equal to or smaller than a predetermined threshold value , it is determined that similarity between the synthesized sub - band and edge image is high . note that the block size and threshold value are set in correspondence with precision required for search . when the sum of the absolute values of the differences exceeds the predetermined threshold value , the comparison unit 5 reads encoded data that belong to a lower bit plane from the input unit 2 , and executes the same processes as above . since larger coefficients are concentrated on the edge of an original image , the coefficients of the synthesized sub - bands undergo comparison in turn from upper bit planes in units of bit planes . this means portions with high edge intensity are preferentially compared . as a result , the shape of an object contained in an image can be compared without completely decoding the encoded data , thus efficiently implementing a search process . when the comparison result between the edge image and synthesized sub - band indicates high similarity , the comparison unit 5 sends a control signal to the decoder 6 , as described above , to make it read out and decode the bitstream of the corresponding image from the image database 1 . hence , the processes in the order opposite to those shown in fig2 are executed in the decoder 6 to reconstruct an image , and the reconstructed image is displayed on the display unit 7 . in the first embodiment , the size or resolution of the shape image is adjusted to that of the sub - band read from the bitstream . however , in the second embodiment , comparison is made without adjusting their sizes or resolutions . in this embodiment , assume that the shape information generation unit 4 generates an edge image having an arbitrary size . the comparison unit 5 segments data to be compared into regions , and compares the segmentation results to check similarity . fig9 and fig1 a to 10 d are respectively a flow chart and views for explaining the region segmentation method . in region segmentation , the bit plane of an image or sub - band of interest is recursively segmented , and that segmentation information is output as a 1 - bit flag . the flow of this process will be explained below with reference to the flow chart in fig9 . in step s 301 , the region of interest is initialized . this region corresponds to an edge image input from the shape information generation unit 4 or the bit plane of a coefficient read from the bit stream . in step s 302 , the current region is scanned , and if ratio of pixels with a value ‘ 1 ’ exceeds a predetermined ratio , segmentation information ‘ 1 ’ is output in step s 304 . otherwise , segmentation information ‘ 0 ’ is output in step s 303 , thus ending region segmentation . it is then checked in step s 305 if the current region size is equal to or larger than a predetermined size . if the current region size is equal to or larger than the predetermined size , the current region is segmented into four regions having nearly the same sizes in step s 306 , and the processes in step s 301 and the subsequent steps are recursively executed for each of the four segmented regions . otherwise , bit information in the region is output in step s 307 . fig1 b to 10 d show the flow of region segmentation when an 8 × 8 ( pixel ) region shown in fig1 a undergoes the aforementioned processes . if the predetermined ratio in step s 302 is “ the presence of one or more pixels with a value ‘ 1 ’′”, the region shown in fig1 a is segmented into four sub - regions r 1 , r 2 , r 3 , and r 4 , as shown in fig1 b . the same processes are executed for each sub - region , and the region r 1 is further segmented into regions r 11 , r 12 , r 13 , and r 14 , as shown in fig1 c . if the predetermined size in step s 305 is 3 × 3 pixels , each of these four regions is not further segmented , and bit data of the regions r 11 , r 12 , r 13 , and r 14 are output . the sub - region r 2 is then subjected to region segmentation , and is also segmented into four regions , as shown in fig1 d . after that , the same processes are done for the sub - regions r 3 and r 4 . the comparison unit 5 compares the region segmentation information obtained in this manner . when images to be compared have similar ‘ 1 ’- bit distributions , nearly equal region segmentation information is obtained . hence , a similar image can be detected . since region segmentation information is compared , the images to be compared need not have equal image sizes . furthermore , by appropriately selecting region segmentation conditions , comparison can be implemented with desired precision . in the above description , region segmentation information is compared as needed . since region segmentation generates four sub - regions , a quaternary tree may be temporarily formed based on these regions , and the nodes of the quaternary tree may be compared . in each of the above embodiments , the bitstream of an encoded and compressed image consists of discrete wavelet transform coefficients . alternatively , the bitstream may consist of coefficients obtained by other transforms , e . g ., sub - band segmentation . even when discrete cosine transform coefficients are used , comparison can be made by spatially re - arranging the coefficients upon region comparison . in each of the above embodiments , quantized coefficients are entropy - encoded upon encoding . alternatively , coefficients may be replaced by region segmentation information described in the second embodiment upon encoding . in this case , since a bit sequence obtained by segmenting an edge image into regions and the bitstream of an encoded and compressed image can be directly compared with each other in comparison in the search process , the search process can be implemented at higher speed . as many apparently widely different embodiments of the present invention can be made without departing from the spirit and scope thereof , it is to be understood that the invention is not limited to the specific embodiments thereof except as defined in the appended claims .