Patent Publication Number: US-8532431-B2

Title: Image search apparatus, image search method, and storage medium for matching images with search conditions using image feature amounts

Description:
BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The present invention relates to an image search apparatus and an image search method, and a storage medium thereof in which a feature amount for image search is inputted and an image is searched under the search conditions for the feature amount. 
     2. Description of the Related Art 
     At present, a digital camera or a portable telephone with camera has widespread, whereby the chance for taking a digital image increases. On the other hand, the storage media using a non-volatile RAM such as a CF (Compact Flash (registered trademark)) card, an SD (Secure Digital (registered trademark)) card or a memory stick (registered trademark) tends to have a larger capacity. Along with this, a greater number of images are stored in the media. Also, there is arranged a use environment in which the taken image is read into an owned PC (Personal Computer), and stored in an HDD (Hard Disk Drive) unit for browsing or printing. 
     Recently, the applications for supporting the image browsing or image selection operation as image management software are increasing. Some applications provide a file management function using an Exif (Exchangeable Image File Format) (registered trademark) standardized by JEIDA. 
     The Exif provides a function of storing the shooting information in a format of Exif Tag. With this Exif tag, the information such as shooting time, exposure amount, focal length and WB (White Balance) can be known later. 
     For example, a UI (User Interface) is provided through which the image can be simply searched according to the shooting time by sorting the images managed by the shooting time and linking them with the calendar. 
     Also, the image management software provides the user with another function of adding arbitrary tag information. With such image management software, the user can add a keyword to one or more images selected by the user. The keyword may be any string. For example, a “wedding ceremony” or an “entrance ceremony” may be inputted as the keyword. 
     In this manner, by adding beforehand the keyword to the image, the user can perform the search by inputting the keyword such as wedding ceremony or entrance ceremony. 
     However, as the number of images increases, the user has more load to add the keywords of various strings to the images, whereby it is difficult to add the keywords that can classify the images simply. 
     Also, when the image is searched by keyword, the keyword for specifying the image may be long or a combination of plural strings. 
     For example, consider a case of searching and finding an image  1001  as shown in  FIG. 10 . The image  1001  has the keywords of “Mr. A” and “Mr. B” appended as the Tag information  1002 . But the other image  1003  has also the same keywords appended as the Tag information  1004 . 
     In such a state, if the search is made according to the keywords of “Mr. A” and “Mr. B”, two images  1001  and  1003  are obtained as the search results. 
     However, actually, the image  1001  has Mr. A on the left side of this image and Mr. B on the right side, which are of the same size, while the image  1003  has two persons in different arrangement and face size. 
     Accordingly, when only the image  1001  is searched, it is required to add the detailed information regarding the composition such as “Mr. A”, “Mr. B”, and “Mr. A on the right side”. However, it is necessary that the representation regarding the composition is systematically added even personally at the time of appending the tag. Also, when another person makes the search, the analysis itself for the keyword and the search itself can not be performed unless the way of appending the keyword is unified. 
     Further, if information such as the size of each face is not added to the tag, it is difficult to limit the search result. 
     In this manner, to search the image by keyword, it is sought to add the systematical keyword and add the detailed composition information. It is difficult for the general user to make such things steadily. 
     As described above, the invention for solving a problem of searching the image by keyword was disclosed in Japanese Patent Laid-Open No. 2000-076268 (hereinafter referred to as a document 1) and Japanese Patent Laid-Open No. 2001-084274 (hereinafter referred to as a document 2), for example. 
     The document 1 disclosed a method in which the feature amount of the image drawn by the user is obtained and the image having the high degree of similarity with the feature amount is displayed as the search result. With this method, the user can input the search conditions as illustration. Accordingly, the method can give the higher representation ability for searching than the keyword. 
     Also, the document 2 disclosed a method for searching the image by inputting a simple graphic such as circle, triangle or rectangle and obtaining the degree of agreement with the subject in the image. 
     With both the techniques as disclosed in the documents 1 and 2, the feature amount of the illustration image inputted by the user is obtained, and the image having higher degree of similarity with the feature amount is searched from an image database (hereinafter denoted as an image DB) to display the search results. 
     The images taken by a photographing apparatus such as a digital camera include the horizontally shot image  1001  and the vertically shot image  1003 , as shown in  FIG. 10 . Especially in the case of the vertically shot image  1003 , the user may rotate the photographing apparatus by 90° clockwise or counterclockwise in taking the image. 
     In the normal case, the shooting data stored as image data is generally stored as horizontally oriented data, irrespective of the orientation at the time of shooting, because the image pickup device for the photographing apparatus is mostly horizontally oriented. Accordingly, the vertically shot image  1003  is stored as the image rotated by +90° or −90° as the horizontally oriented image like the horizontally shot image  1001 .  FIG. 10  shows the image  1003 ′ rotated by +90° clockwise. 
     Accordingly, when the image search is performed by the method as disclosed in the document 1 or 2, there is a problem that the desired result can not be obtained only by directly applying the conditions inputted by the user to the image data. 
     That is, even if the search conditions are inputted at an aspect (length-to-width) ratio of the image limited in the case of searching the image where two persons sit side by side, the images  1001  and  1003 ′ can not be searched at the same time. Also, when the image  1003 ′ is rotated into alignment in the upper, lower, left and right, and stored as the image  1003 , these three images can not be searched. 
     With these conventional methods, when the images taken under various conditions such as plural aspect ratios, horizontal shooting and vertical shooting are collectively selected and searched, the search conditions adaptable to all the images can not be specified, whereby there was a problem that the search can not be made as intended. 
     SUMMARY OF THE INVENTION 
     Thus, in order to solve the above-mentioned problems, an image search apparatus and an image search method and its storage medium according to the invention have the following constitution. 
     In the first aspect of the present invention, there is provided an image search apparatus comprising search object image designation means for designating a search object image, search condition input means for inputting the search conditions, feature amount extraction means for extracting a feature amount from the search object image, feature amount transformation means for transforming the feature amount to be adaptable to the inputted search conditions, and determination means for determining whether or not the search object image is matched with the search conditions using the feature amount after transformation. 
     In the second aspect of the present invention, there is provided an image search method for use in an image search apparatus, the method comprising a search object image designation step of designating a search object image, a search condition input step of inputting the search conditions, a feature amount extraction step of extracting a feature amount from the search object image, a feature amount transformation step of transforming the feature amount to be adaptable to the inputted search conditions, and a determination step of determining whether or not the search object image is matched with the search conditions using the feature amount after transformation. 
     In the third aspect of the present invention, there is provided a computer readable storage medium storing a program for performing an image search method on a computer, the method comprising a search object image designation step of designating a search object image, a search condition input step of inputting the search conditions, a feature amount extraction step of extracting a feature amount from the search object image, a feature amount transformation step of transforming the feature amount to be adaptable to the inputted search conditions, and a determination step of determining whether or not the search object image is matched with the search conditions using the feature amount after transformation. 
     With the invention, it is possible to provide an image search apparatus or method capable of making the search by designating the search conditions at one time, when the images taken under various conditions such as plural aspect ratios, horizontal shooting and vertical shooting are collectively selected for the search. 
     Further features of the present invention will become apparent from the following description of exemplary embodiments (with reference to the attached drawings). 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram of an image search apparatus of an embodiment in accordance with the present invention; 
         FIG. 2  is a flowchart for image search in the first embodiment; 
         FIG. 3  is a diagram showing one example of a UI for an image search application in the first embodiment; 
         FIG. 4A  is a diagram showing one example of the UI for a search condition input dialog and a search condition input coordinate system in the first embodiment; 
         FIG. 4B  is a diagram showing one example of the UI for the search condition input dialog and the search condition input coordinate system in the first embodiment; 
         FIG. 5A  is a diagram for explaining a method for changing a face icon in the first embodiment; 
         FIG. 5B  is a diagram for explaining the method for changing the face icon in the first embodiment; 
         FIG. 6  is a diagram for explaining the transformation of an image coordinate system in the first embodiment; 
         FIG. 7  is a diagram for explaining the transformation of the image coordinate system in the first embodiment; 
         FIG. 8  is a diagram for explaining the transformation of the image coordinate system in the first embodiment; 
         FIG. 9  is a diagram for explaining the transformation of the image coordinate system in the first embodiment; and 
         FIG. 10  is a diagram showing an example of the conventional image search by keyword. 
     
    
    
     DESCRIPTION OF THE EMBODIMENTS 
     The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. 
     &lt;First Embodiment&gt; 
       FIG. 1  shows a block diagram of an image search apparatus of an embodiment in accordance with the present invention. 
     Though it is supposed here that a PC is employed as the image search apparatus for the explanation, one or more general-purpose computers or dedicated devices other than the PC may be employed. In the following, the image search will be described in which the conditions for searching the image include the person, especially face that is one of the main subjects for photograph. 
     A CPU  101  is a central processing unit (Central Processing Unit) for controlling the other functional blocks or devices. A bridge section  102  provides a function of controlling the exchange of data between the other functional blocks and the CPU  101 . 
     A ROM (Read Only Memory)  103  is a read only non-volatile memory, in which a program called a BIOS (Basic Input/Output System) is stored. The BIOS is the program firstly executed when the image search apparatus is started, and controls the peripheral devices such as a secondary storage device  105 , an output device  107  and an input device  109 . 
     A RAM (Random Access Memory)  104  provides a high speed readable/writable storage area. 
     The secondary storage device  105  is an HDD that provides a large capacity of storage area. If the BIOS is performed, an OS (Operating System) stored in the HDD is executed. The OS provides the basic functions available on all the applications, the management of applications and a basic GUI (Graphical User Interface). The application can provide a UI for implementing the specific functions of application itself by combining the GUIs provided by the OS. The executable program for the OS or other applications or working data is stored in the RAM  104  or the secondary storage device  105 , as needed. 
     A display control section  106  performs the control for displaying the image data of GUI generated as the result of a user&#39; operation on the OS or application on the display device  107 . The display device  107  may be a liquid crystal display or a CRT (Cathode Ray Tube) display. 
     An I/O control section  108  provides an interface with a plurality of input devices  109 . The typical interfaces include a USB (Universal Serial Bus) and a PS/2 (Personal System/2). 
     An input device  109  such as a keyboard or a mouse inputs an instruction on the user&#39;s will into the image search apparatus. Further, it may transfer image data by connecting to a digital camera or a storage device such as a USB memory from them. 
       FIG. 2  shows a flowchart of an embodiment in accordance with the present invention. 
     The case that an image search function of the image search apparatus according to this embodiment is provided as one function of a GUI for application will be described bellow. Therefore, an instruction of the user is inputted from the input device  109  such as a mouse or a keyboard, whereby an interactive operation is enabled. A processing flow as shown in  FIG. 2  is one example of flow when the user searches the image, but actually because of the interactive operation, an instruction of returning to the beginning from the middle of the flow may be made. To simplify the explanation here, a typical operation flow will be only described below. 
       FIG. 3  shows a UI at the time of starting an image search application  301  performed by the image search apparatus. Referring to  FIG. 3 , an operation of selecting an image at an image selection step of S 01  in  FIG. 2  will be firstly described below. 
     The image search application  301  (search object image designation means) is composed of three areas for a folder selection UI  302 , an image list UI  303  and a selected image list UI  304 . A pointing UI  306  (a so-called pointer) is a UI, which can move in accordance with an operation of the input device  109  such as a mouse, and input a user&#39;s operation into the image search application  301 . 
     The folder selection UI  302  provides a function of selecting a store location of image data stored in the image search apparatus. In  FIG. 3 , a certain store location is designated by the pointing UI  306 . 
     The image list UI  303  displays a list of image data at the store location selected by the folder selection UI  302 . The selected image list UI  304  is an area only for displaying the image selected by the user or the image searched according to the designation of the user. 
     If the user selects a desired folder in the folder selection UI  302  by moving the pointing UI  306  at S 01 , a list of image stored within the folder is displayed in the image list UI  303 . 
     If the desired image for the next processing object without search is selected by the pointing UI  306 , the selected image is displayed in the selected image list UI  304 . For example, if Image 1   305  is selected, Image 1   305  is displayed in the selected image list UI  304 . At this time, Image 1   305  is internally registered as the object image for the next processing in the list. Though not displayed, a button for selecting all the images within the folder may be prepared. Also, a different folder may be designated to additionally select the image in the folder. 
     However, in performing the search as will be described later, a plurality of folders are firstly selected. If the selection is completed, the processing moves to the step S 02  at which the search conditions are inputted. To move to the step of the search condition input, a search menu  307  or a search button  308  for the search application  301  is selected, so that a search dialog  401  (i.e. a display element of search condition input means) appears as shown in  FIG. 4 . 
     Herein, it is supposed that the main subject to be noticed in searching the image is the person&#39;s face in the continuing explanation. The person&#39;s face is one of the subjects with the highest frequency of shooting in the photographs. Accordingly, in searching the image, the very effective search conditions may include whether the person exists in the image, how many persons there are and where the person exists in the image. 
     Referring to  FIG. 4 , an input method for the search conditions performed at S 02  in  FIG. 2  will be described below. 
     In the search dialog  401 , the number of faces  402  and the face position  403  can be designated. If the check box for the number of faces  402  is checked, the number of faces existent in the image can be designated. Herein, if the maximum number of faces and the minimum number of faces are inputted, the condition satisfying
 
Minimum number of faces≦Number of faces in the image≦Maximum number of faces
 
can be set up.
 
     Next, if the check box for the face position  403  is checked, the face position can be designated. If an additional button  404  is selected, a face icon  409  appears in a face position input area  408 . The face icon  409  can be selected by the pointing UI  410  to change the position in the face position input area  408 . 
     If the additional button  404  is selected plural times, a plurality of face icons  408  can be set up. Also, the face icon  408  which is supposedly unnecessary may be selected by the pointing UI  306  and removed from the face position input area  408  by selecting a delete button  405 . 
     Further, a face icon  501  has two clip points  502  and  503 , as shown in  FIG. 5 . A clip point  502  is used to adjust the size of the face icon  501 . A clip point  503  is used to adjust the inclination of the face icon  501 . 
       FIG. 5A  shows how the face icon  501  is enlarged by selecting the clip point  502  with the pointing UI  504  and moving the pointing UI  504  right downward. Similarly,  FIG. 5B  shows how the face icon  501  is rotated clockwise by selecting the clip point  503  with the pointing UI  504  and moving the pointing UI  504  obliquely right downward. 
     By providing the functions as described above, it is possible to simply specify such complex search conditions for the image that the faces of designated size exist on the left in the image, with the number of faces being from 1 to 20, for example, as shown in  FIG. 4B . 
     In the face position input area  408 , a coordinate system as indicated at  400  is defined. This coordinate system has the origin at the center point (x,y)=(0,0) on the screen, where the upper side y=−100, the lower side y=100, the left side x=−100, and the right side x=100. 
     Accordingly, the face designated by the face icon  409  has the center (x,y)=(−60,0), in which the size of face is 80 and the inclination is 0°. Herein, the size of face means the length of one side in the rectangular area of the face icon  409 . The rotation angle is defined to be positive in the clockwise direction with reference to the upper direction on the paper of  FIG. 4 . 
     If all the specifications are ended, an OK button  406  is selected to settle the conditions, and the operation goes to S 03 . Also, if a Cancel button  407  is selected, the designation of the search conditions is canceled, and the operation can return to S 01 . 
     Next, the feature amount of the main subject included in the search object image selected at S 01  is calculated at S 03  (feature amount extraction step) in  FIG. 2 . Herein, the feature amount means the position, size and inclination of face in the image designated at S 02 . 
     Various methods for detecting the face in the image have been conventionally proposed. For example, there is an invention as disclosed in Japanese Patent Laid-Open No. 2002-183731 by the present applicant. With this invention, an eye area is detected from an input image, and the peripheral part around the eye area is made a face candidate area. And for this face candidate area, the gradient of gradation distribution for each pixel and the weight based on the gradient of gradation distribution are calculated. Using these values, the gradient of gradation distribution for the ideal preset face reference image and the weight based on the gradient of gradation distribution, the face candidate area and the face reference image are compared. A method for judging that the input image has the face area if the mean value of angle between these gradients or the weighted mean value is less than or equal to a predetermined threshold is described. 
     Also, in Japanese Patent Laid-Open No. 2003-30667, first of all, a flesh color area is detected from the image, and the iris color pixel of the human is detected in the same area, whereby the position of the eye can be detected. 
     Further, in Japanese Patent Laid-Open No. 8-63597, the matching degrees of the image with a plurality of templates having the facial shape are calculated, and the template having the highest matching degree is selected. And if the highest matching degree is greater than or equal to a predefined threshold, an area within the selected template is made the face candidate area. In this manner, the position of the eye can be detected using the above template. 
     Further, in Japanese Patent Laid-Open No. 2000-105829, first of all, a nose image pattern is prepared as the template, and the entire image or a designated area of the image is scanned, whereby the most matched position is outputted as the position of nose. Considering an area above the position of nose as the area where the eye exists, an eye existent area is scanned and matched with an eye image pattern as the template, and then an eye existent candidate position set that is a set of pixels having greater matching degree than a certain threshold is obtained. Further, a consecutive area included in the eye existent candidate position set is divided into clusters, and the distance between each cluster and the nose position is calculated. The cluster having the shortest distance is decided as the cluster where the eye exists, whereby the organ position of person&#39;s face can be detected. 
     Besides, various methods for detecting the face and the organ position in the face have been proposed. For example, some methods are proposed in Japanese Patent Laid-Open No. 8-77334, Japanese Patent Laid-Open No. 2001-216515, Japanese Patent Laid-Open No. 5-197793, and Japanese Patent Laid-Open No. 11-53525. Also, other methods are proposed in Japanese Patent Laid-Open No. 2000-132688, Japanese Patent Laid-Open No. 2000-235648, Japanese Patent Laid-Open No. 11-250267, and Japanese Patent No. 2541688. In the present invention, any of those methods may be employed. Also, the method for detecting the face and the organ position in the face is not limited to those as described above, and any other method may be employed. Since the conventional methods for detecting the face and the organ position in the face are disclosed in various literatures and patents, the detailed explanation is omitted. 
     The number of person&#39;s faces and the coordinates of the face area in the original image data are obtained by the above methods, and the face coordinate data of the detection result is obtained. Herein, it is supposed that the face area is a rectangular area as the detection result and the coordinates of four vertexes are outputted. The face detection is performed for the images selected at S 01  in  FIG. 2 , whereby the face detection result is stored. Two or more face detection results may be obtained. As a matter of course, the face coordinates detected at S 01  are the coordinates in each selected image. Thus, it is required that the coordinates are associated with the coordinate system for the face position input area  408  designated in the search dialog  401  as used at S 02 . 
     Therefore, at S 04 , a processing for transforming the face detection coordinates detected at S 03  into the coordinate system for the face position input area  408  is performed to adapt to the search conditions. Referring to  FIGS. 6 and 7 , the transformation method will be described below. 
       FIG. 6  is an example of a horizontally oriented image, and  FIG. 7  is an example of a vertically oriented image. They are represented in two dimensions, and have the coordinate axes X and Y in the directions as indicated at  604  and  704  respectively. The coordinate systems  601  and  701  are coordinate systems for the search dialog  401 . The coordinate systems  601  and  701  have the origin at the center, and can take the values of x and y from −100 to 100. 
     The coordinate systems  602  and  702  have the numbers of pixels W and H horizontally and vertically. The coordinate systems  602  and  702  have the origin (0,0) at the upper left point and can take the values up to the lower right point (W,H). The coordinate systems  603  and  703 , like the coordinate systems  601  and  701 , have the origin at the center, and can take the values of X and Y from −100 to 100, in which the image is fitted in the coordinate system. 
     Any point P(x,y) in the coordinate systems  602  and  702  is represented by the point P′(x′,y′) in the coordinate systems  603  and  703  which is relatively at the same position. A transformation expression at this time is an expression (1) for x and an expression (2) for y as follows. 
     
       
         
           
             
               
                 
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     Using the transformation expressions (1) and (2), the coordinate values of all the faces detected at S 03  are transformed. 
     At S 05 , the degree of similarity between the search conditions specified at S 02  and information obtained from the coordinates of the faces transformed at S 04  is computed. The search conditions include the number of faces existent in the image (value designated by the number of faces  402 ) and the coordinate value of the face icon  409  (designated by the face position  403 ). Herein, a plurality of face icons  409  may be designated. 
     At first, it is determined whether or not the number of faces detected at S 03  satisfies the number of faces designated at S 02 . If this condition is satisfied, the degree of similarity between the coordinates of all the face detection results and the coordinates of the face icon  409  is computed. The degree of similarity can be computed using the sum of distances between four vertexes of the face icon  409  and corresponding four vertexes of the face detection results, or the degree of agreement in the central points, the sizes of the rectangles and the angles (inclinations) of the rectangles computed respectively from the four vertexes of the face icon  409  and corresponding four vertexes of the face detection results. 
     At S 06 , it is determined whether or not the number of faces satisfies the condition and there is any face determined to be similar. That is, it is determined whether or not the feature amount after transformation is matched with the search conditions. The determination is made by deciding beforehand a predetermined threshold and comparing its value with the degree of similarity computed at S 05 . Herein, if there is any face with the degree of similarity exceeding the threshold, the processing goes to S 07 , where the image is registered in the list. On the other hand, if not, the processing goes to S 08 . 
     At S 08 , it is determined whether or not all the images selected at S 01  are processed. If all the images are not processed, the processing goes to S 03  to process the next image. If all the images are processed, the processing goes to S 09 , whereby the search results so far obtained are displayed on the display device  107 . 
     The display of the search results can be implemented by updating the display of the selected image list UI  304  in the image search application  301 . At this time, the results displayed in the selected image list UI  304  can be displayed in descending order of the degree of similarity by sorting the search results based on the degree of similarity at S 07 . 
     While the image search apparatus with the person&#39;s face as the search conditions has been described above, other search conditions may be employed. For example, a personal recognition method for recognizing the person may be adopted, whereby the search with higher added value is enabled. In the case of employing the personal recognition, when the face icon  409  is added by the addition button  404  at S 02 , a plurality of face icons  409  linked with the person may be pre-selected, and the icon for the person to be searched from them may be designated. 
     Also, any body (object) as the noticed subject, not limited to the face or person, may be designated. For example, a car and a building may be considered. Using a detector or a detection method for detecting each object, the search can be made in the same manner as for the face. 
     Also, some kinds of photographing apparatuses can detect the inclination at the time of shooting and write it in Exif Tag. This Tag information is called Orientation. By analyzing this information, the image data can be aligned in the upper, lower, left and right directions and displayed. At the time of search, if the user chooses whether or not to use this information, the search can be made under the consistent search conditions without regard to the image direction. 
     In the image search apparatus of this embodiment, the search results may not be intended by the user, after S 09  where the image search results are displayed under the search conditions inputted at S 02 . At this time, to make better the search results, a narrowing search may be provided. The narrowing search is a method for making the search by further adding the search condition to the search results. The search dialog  401  may be provided with a check box of the narrowing search, not shown, and the search conditions may be added or modified by adding the face detection icon  409  or changing the designation of the number of faces  402  and the like. Thereafter, the search may be performed again for the image with the previous search results, and repeated until the intended search results are obtained. 
     At this time, a search assist function of displaying an auxiliary message such as “Is the number of faces matched?” or “Is the face direction matched?” if the narrowing search check box, not shown, is checked may be provided. Also, though the coordinate values of the faces detected at S 03  are transformed in the above embodiments other way round, the coordinate value of the face icon  409  may be transformed, and the degree of similarity between the coordinate values of the faces detected at S 03  and the transformed coordinates of the face icon  409  may be computed. 
     &lt;Other Embodiments&gt; 
     In the first embodiment as described above, the photographed image including the noticed subject is searched from the photographed images having different aspect ratios, in which the face icon  409  is arranged in the face position input area  408  with the fixed aspect ratio so that the search conditions can be inputted. However, the X and Y axes of the image are aligned at the aspect ratio of the face position input area  408 , whereby the scale up and down ratios along the X and Y axes may be different. Accordingly, the coordinates are consistent at only the center point, and may be necessarily shifted in the other areas. 
     Generally, even with the specifications of such search conditions that the search precision is high near the center and rough on the periphery, they do not have a practical problem. Therefore, in another embodiment, the search conditions can be inputted more effectively by making the coordinate transformation as shown in  FIG. 8 . 
     A coordinate system  801  of the above image is the coordinate system for the image in which the numbers of pixels in width and length are W and H respectively. This coordinate system  801  has the origin (0,0) at the upper left point and can take the values up to the lower right point (W,H). 
     The image coordinate system  801  is transformed into a coordinate system  802  that has the origin at the center and can take the values of X and Y from −100 to 100, like the coordinate system for the search dialog  401 . 
     In the coordinate system  802  after transformation, the image is transformed for the smaller one (short side direction) of the horizontal and vertical numbers of pixels as in the first embodiment. In  FIG. 8 , since the vertical number of pixels is smaller than the horizontal number of pixels, the coordinates for the Y axis are transformed in accordance with the expression (2). 
     On the other hand, the interval of coordinates in the X axis direction that is the long side direction with greater number of pixels is transformed into the same coordinate interval as the Y axis within a predetermined range (herein ±60) In  FIG. 8 , the range corresponds to an area  803 . Outside this area, the interval is wider toward the periphery, and ±100 at both ends. The relationship between x before transformation and x′ after transformation is represented by the following expressions (3), (4) and (5). 
     
       
         
           
             
               
                 
                   
                       
                   
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       FIG. 9  illustrates a graph showing the correspondence between x and x′ at this time. In this manner, through such a transformation of making the equal magnification in length and width near the center of the coordinate system and the variable magnification near the ends, it is possible to provide an environment where the search conditions can be easily inputted intuitively, even if the aspect ratio of the face position input area  408  and the aspect ratio of the image to be searched are different. As a matter of course, in the case of the vertically oriented image, the transformations for the X axis and the Y axis may be exchanged. 
     Also, in determining the degree of similarity at S 06 , the tolerance of determination is made greater toward the periphery, namely, the determination for differences is loosened when the specified search conditions are compared with the feature amounts such as the position, size and angle of face as previously described. Thereby, the search is possible in consideration of input errors of the search conditions which are greater toward the periphery. 
     The object of the present invention is achieved by causing a computer (or CPU or MPU) of the system or apparatus to read and execute a program code from a storage medium storing the program code for implementing a procedure of the flowchart as shown in the above embodiments. In this case, the functions of the above embodiments can be implemented by the program code read from the storage medium. Therefore, this program code and the computer readable storage medium recording or storing the program code may constitute one of the present inventions. 
     The storage medium for supplying the program code may be a floppy disk, a hard disk, an optical disk, an optical magnetic disk, a CD-ROM, a CD-R, a magnetic tape, anon-volatile memory card or a ROM, for example. 
     Also, the functions of the above embodiments can be implemented by executing the read program code on the computer. Also, the execution of the program may include a case where an OS or the like operating on the computer performs a part or all of the actual processing, based on the instructions of the program code. 
     Moreover, the functions of the above embodiments can be also implemented using a function extension board inserted into the computer or a function extension unit connected to the computer. In this case, first of all, the program read from the storage medium may be written into a memory provided for the function extension board inserted into the computer or the function extension unit connected to the computer. Thereafter, a CPU or the like equipped on the function extension board or function extension unit may perform a part or all of the actual processing, based on the instructions of the program. The functions of the above embodiments can be also implemented through the processing of the function extension board or function extension unit. 
     While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. The scope of the following claims is to be accorded the broadest interpretation so as to encompass all such modifications and equivalent structures and functions. 
     This application claims the benefit of Japanese Patent Application No. 2007-123665, filed May 8, 2007, which is hereby incorporated by reference herein in its entirety.