JP2005196529A - Image classification program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image classification program for easy use of a classified image file. <P>SOLUTION: When a folder storing the image file to be classified is selected, an image file inside the folder is classified into groups of the same free character, and then, classified into groups of the sequential file number. The files are classified further into groups of the same date information, and the grouped files are stored in each folder after a specific folder name is given to each group finally classified. In this way, classification close to a scene of image photographing can be carried out, and use can be facilitated afterward. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to an image classification program, and more particularly to an image classification program for classifying image files into categories.

  A digital camera uses an imaging device such as a CCD instead of film to convert an image into an electrical signal, digitizes the data, and records the data on a recording medium such as a memory card. Since the image data photographed by this digital camera is digitized, it can be easily taken into a personal computer (personal computer), and the memory card also erases the recorded image data, so that However, since it can be used, generally, image data taken with a digital camera is taken into a personal computer and managed by the personal computer.

  However, as the amount of image data captured by the personal computer increases, the management becomes more difficult, and there is a problem that it is difficult to quickly find the image that you want to see.

In order to solve such problems, Patent Document 1 discloses that when storing image data, a predetermined category (time stamp, date, shooting condition, resolution, shape, shape) is determined from basic attributes attached to the image data. Etc.), an electronic album apparatus that automatically classifies and stores image data has been proposed.
Japanese Patent Laid-Open No. 2003-199028

  However, since the electronic album apparatus disclosed in Patent Document 1 simply classifies image data by a category such as a time stamp, there is a possibility that the images in the classified category have little difference or are categorized as irrelevant images. There is. For example, the classification by date and the classification by time have the disadvantage that the classification by time is merely a more detailed classification of the classification by date and date, and it becomes a simple set inclusion relationship. In addition, the classification based on the file capacity and resolution has a drawback that images taken at completely different dates and events are in the same category, and the relevance of images in the category is reduced.

  The present invention has been made in view of such circumstances, and an object thereof is to provide an image classification program that allows easy use of image files after classification.

  The invention according to claim 1 is an image classification program for classifying an image file having a file name combining free characters and a file number in order to achieve the object, and obtains a plurality of image files to be classified. A step of classifying the acquired plurality of image files for each group of the same free characters, a step of classifying the image files classified for each group of the same free characters for each group of consecutive file numbers, A step of further classifying the image files classified into groups having consecutive file numbers into groups having the same date information, and assigning a specific folder name to each finally classified group, and storing the image files in the folder And an image classification program for causing a computer to execute the steps

  According to the present invention, when a plurality of image files to be classified are acquired, the acquired plurality of image files are classified into groups of the same free character, and further classified into groups of consecutive file numbers. Then, the images are further classified into groups having the same date information, and a specific folder name is given to each finally classified group, and the image file is stored in the folder. As a result, the classification becomes close to the scene of image shooting, and it becomes easy to use later.

  In order to achieve the above object, the invention according to claim 2 further includes a group having the same time information when the number of image files in the group having the same date information exceeds a preset number of files. The image classification program according to claim 1, further comprising a step of classifying each image.

  According to the present invention, for image files classified for each group having the same date information, when the number of image files in each group exceeds a preset number of files, the same time information is further provided. Classified by group. As a result, the classification becomes closer to the scene of image shooting, and it is easy to use later.

  According to a third aspect of the present invention, there is provided an image classification program for classifying image files in order to achieve the object, the step of acquiring a plurality of image files to be classified, and the plurality of acquired image files For each group having the same year information, a step for further classifying the image files classified for each group having the same year information for each group having specific shooting information, and for each group finally classified An image classification program for causing a computer to execute a step of assigning a specific folder name and storing an image file in a folder is provided.

  According to the present invention, when a plurality of image files to be classified are acquired, the acquired plurality of image files are classified into groups having the same year information, and further classified into groups having specific photographing information. Then, a specific folder name is assigned to each classified group, and the image file is stored in the folder. As a result, the classification becomes close to the scene of image shooting, and it becomes easy to use later.

  According to a fourth aspect of the present invention, in order to achieve the object, the specific photographing information is presence / absence of strobe light emission, subject distance, or light source type. Provide a program.

  According to the present invention, the image files classified for each group having the same year information are further classified by the presence / absence of strobe light emission, subject distance, or light source type. As a result, the classification becomes closer to the scene of image shooting, and it is easy to use later.

  According to a fifth aspect of the present invention, there is provided an image classification program for classifying image files in order to achieve the object, the step of acquiring a plurality of image files to be classified, and the plurality of acquired image files If there is an image file having date information of an event set in advance among the image files classified for each group having the same month information, the date information There is provided an image classification program for causing a computer to execute a step of classifying each group having a file name and a step of assigning a specific folder name to each finally classified group and storing an image file in the folder.

  According to the present invention, when a plurality of image files to be classified are acquired, the acquired plurality of image files are classified for each group having the same month information. Then, if there is an image file with date information of a preset event in the group having the same month information that is classified, it is classified for each group that has the date information, and specified for each classified group The folder name is assigned and the image file is stored in the folder. As a result, the classification becomes close to the scene of image shooting, and it becomes easy to use later.

  According to a sixth aspect of the present invention, there is provided an image classification program for classifying image files in order to achieve the object, the step of acquiring a plurality of image files to be classified, and the plurality of acquired image files For causing a computer to execute a step of classifying each group having latitude and longitude information in a predetermined range, and a step of storing a specific folder name for each classified group and storing an image file in the folder Provide a classification program.

  According to the present invention, when a plurality of image files to be classified are acquired, the acquired plurality of image files are classified into groups each having a predetermined range of latitude and longitude information, and a specific folder name is assigned to each classified group. To store the image file in a folder. As a result, the classification becomes close to the scene of image shooting, and it becomes easy to use later.

  According to the image classification program according to the present invention, the classification of the image is a classification close to the scene where the image was photographed, so that the use of the image file after the classification becomes easy.

  The best mode for carrying out an image classification program according to the present invention will be described below with reference to the accompanying drawings.

  FIG. 1 is a block diagram showing a hardware configuration example of a computer (personal computer) that executes an image classification program according to the present invention.

  The personal computer 10 is a commonly used type of computer, and temporarily stores a central processing unit (CPU) 12 for executing an image classification program according to the present invention, calculation results in the CPU 12, image data, and the like. RAM 14, an operating system (OS), an image classification program according to the present invention, various application programs, a hard disk drive (HDD) 16 for storing image files, etc., and data stored in a CD-ROM A CD-ROM drive 18, a display device 20 for displaying calculation results and image data in the CPU 12, a keyboard for inputting commands and numerical values, an input device 22 such as a mouse, and a memory card 24 storing image files. Memory card for connection And an input / output terminal (for example, a USB terminal) 30 for connection with a network 26 and a digital camera 28 via a communication cable, a modem 32 for communicating with a server through a network, and the like. 34 is connected.

  The image classification program according to the present invention classifies image files stored in a designated folder according to a predetermined rule. The image classification program according to the present embodiment is incorporated in an image browsing program (viewer) that browses image files, and is provided as a function of the image browsing program.

  The image browsing program is installed in the hard disk drive 16 of the personal computer 10 and is loaded from the hard disk drive 16 into the RAM 14 so that execution control by the CPU 12 is performed. The program stored in a CD-ROM or the like may be read and executed by the CD-ROM drive 18 or may be downloaded from a network and executed.

  When the image browsing program is activated, a main window of the image browsing program is displayed on the display device 20 as shown in FIG.

  The main window includes a folder tree display area displayed on the left side of the screen and a thumbnail display area displayed on the right side of the screen.

  In the folder tree display area, folders in the personal computer 10 are displayed hierarchically. When a folder displayed in the folder tree display area is selected, the image files stored in the selected folder are displayed in a list in thumbnail format in the thumbnail display area.

  If there is no image file in the selected folder, nothing is displayed in the thumbnail display area. If there are more folders in the selected folder, a list of folder icons is displayed. FIG. 2 shows a display example when a folder (“100_FUJI”) exists in the selected folder (“DCIM”).

  When an arbitrary image file is selected (double-clicked) from the image files listed in the thumbnail format in the thumbnail display area, the selected image file is enlarged and displayed in another window.

  Also, when the slide show function is executed, the image files stored in the selected folder are automatically played back at regular intervals.

  In this image browsing program, image file classification (execution of the image classification program) is performed by selecting a folder to be classified and issuing a classification execution instruction. FIG. 3 is a flowchart showing the procedure of the classification process.

  First, a folder to be classified is selected (step S10). Folder selection is performed on the folder tree display frame. That is, it is performed by selecting (double-clicking) a folder to be classified from the folders displayed in the folder tree display frame with the mouse pointer. When a folder to be classified is selected, the image files stored in the selected folder are displayed in a list in the detail display frame as shown in FIG.

  Next, the execution of the classification process is instructed to the folder selected as described above. The instruction to execute the classification process is performed by calling the image file classification function. As shown in FIG. 4, the image file classification function is invoked by selecting “Edit” from the items displayed on the toolbar and selecting “Image File Classification” from the items in the “Edit”. It is.

  When the image file classification function is called up, as shown in FIG. 5, an image file classification dialog box is displayed on the display device 20, and a message asking whether or not classification is necessary is displayed. Here, in order to instruct classification execution, the “execution” icon displayed in the dialog box is selected (clicked) with the mouse pointer, and in order to cancel, the “cancel” icon is selected.

  The CPU 12 determines the presence / absence of an execution instruction based on the input from the mouse (step S11). When the execution of classification is instructed, the classification process of the image file stored in the selected folder is executed.

  The image files are classified based on the file name and date / time information of each image file. First, the image files are classified into groups of the same free character file names (step S12). Next, the files are classified into groups having consecutive file numbers (step S13), and finally are grouped into groups having the same date information (step S14).

  For example, assume that an image file group as shown in FIG. 6 is stored in a selected folder. When the classification process is executed on the image file group stored in this folder, first, grouping is performed for each group of file names having the same free character.

  Here, “free character” refers to a character string prefixed to a file name, and the file name of an image file is generally configured by combining this free character and a file number.

  For example, in the case of the image file number 1 shown in FIG. 6, the file name “FILE0001” is composed of a combination of a free character consisting of four alphabets “FILE” and a four-digit file number “0001”. Has been.

  The file name “OTHER001” of the image file number 17 is configured by combining a free character consisting of five alphabets “OTHER” and a three-digit file number “001”.

  The file name “20031230-001” of the image file number 20 is configured by combining an 8-digit number “20031230-” and a free character consisting of a hyphen and a 3-digit file number “001”. ing.

  In the case of the image file group shown in FIG. 6, there are an image file whose free character is “FILE”, an image file whose free character is “OTHER”, and an image file whose free character is “20031230-”. The image files are classified for each group (the group is classified into three groups: a group whose free characters are “FILE”, a group “OTHER”, and a group “20031230-”).

  Next, the image files grouped for each free character are classified into groups having consecutive file numbers for each group (step S13).

  For example, in the example shown in FIG. 6, when classifying an image file group called “FILE”, the file numbers “0001”, “0002”, “0003”, “0004”, “0015”, “0016”, “0017”, “0018”, “0019”, “0020”, “0035”, “0036”, “0037”, “0038”, “0039”, “0040” There are 16 image files, and the consecutive file numbers are “0001” to “0004”, “0015” to “0020”, and “0035” to “0040”. As for the group of image files “FILE”, the groups whose file numbers are “0001” to “0004”. If, file number and groups of up to "0015" - "0020", the file number is classified into three groups of groups of up to "0035" - "0040".

  In the example shown in FIG. 6, for the group of free characters “OTHER” and the group of “20031230-”, the file numbers of the image files in the group are all serial numbers. Therefore, in this case, the classification process is not performed.

  Next, the image files classified for each group of consecutive file numbers are classified into groups having the same date information (step S14).

  For example, in the example shown in FIG. 6, when the groups of the free character “FILE” and the file numbers “0015” to “0020” are classified, the free character “FILE” and the file numbers “0015” to “0020” are grouped. Since there is an image file having date information 2003/01/01 and an image file having date information 2003/03/03, a group having date information 2003/01/01 and 2003/03 And a group having date information of / 03.

  Further, for example, in the example shown in FIG. 6, when the groups of free characters “20031230-” and file numbers “001” to “026” are classified, the free characters “20031230-” and file numbers “001” to “026” The groups up to and including the image file having date information 2003/11/23, the image file having date information 2003/12/24, the image file having date information 2003/12/25, Since an image file having date information of 12/28 exists, a group having date information of 2003/11/23, a group having date information of 2003/12/24, and date information of 2003/12/25 Group with date information of 2003/12/28 It is classified in the group to be.

  As a result, as shown in FIG. 7, the image file group in the example shown in FIG. 6 includes (1) “FILE0001” to “FILE0004”, (2) “FILE0015” to “FILE0016”, and (3) “FILE0017” to “FILE0020”, (4) “FILE0035” to “FILE0036”, (5) “FILE0037” to “FILE0040”, (6) “OTHER001” to “OTHER003”, (7) “20031230-001” to “20031230-002” , (8) “20031230-003” to “20031230-008”, (9) “20031230-009” to “20031230-023”, (10) “100031230-024” to “20031230-026” Is finally classified.

  Then, a predetermined folder name is assigned to each group of the image files grouped in this way and stored individually in the folder. This folder is created in the folder selected as the classification target, and the folder name includes a predetermined character string (here “Folder”) and a serial number (here “001” to “010”) for each group. )) Is combined with a folder name ("Folder001" to "Folder010"). In the thumbnail display area of the image browsing program displayed on the display device 20, a list of the classified folders is displayed as shown in FIG.

  As described above, according to the image classification program of the present embodiment, the image file group to be classified is classified for each group of the same free characters, and further classified for each group of consecutive file numbers. Sort by groups that have the same date information. As a result, the classification can be made close to the scene of image shooting, and the management of the image file after classification becomes easy.

  In the present embodiment, classification is finally performed by date. However, in a case where a large amount of image files exist only on a specific date, there is a possibility that detailed classification according to the shooting scene cannot be performed. .

  In order to prevent such inconvenience, when image files exceeding a specified number are classified into one group even after classification by date, classification by time may be further performed. For example, after the classification by date, if the number of image files in the classified group exceeds 10, the group is further classified for each group having the same time information. FIG. 9 is a flowchart showing a processing procedure in the case of performing classification based on this time.

  As shown in the figure, after selection of a folder to be classified (step S20), it is determined whether or not a classification execution instruction is given (step S21). Sort into file name groups (step S22). Next, the files are classified into groups having consecutive file numbers (step S23), and further classified into groups having the same date information (step S24).

  Then, it is determined whether or not the number of image files in each classified group exceeds a specified number (here, 10 files) (step S25). If the number exceeds the specified number, the specified number is exceeded. The classification process is executed on the group having the same time information with respect to the group having the image file (step S26). Then, this is set as the final classification, and a predetermined folder name is assigned to each classified group and stored in the folder (step S27).

  On the other hand, if the number of image files in each classified group is equal to or less than the specified number, this is set as the final classification, and a predetermined folder name is assigned to each classified group and stored in a folder (step S27).

  In the example shown in FIG. 6, in the classification up to the group having the same date information, as shown in FIG. 7, 15 image files are classified into the ninth group. Further, the data is classified into groups having the same time information. As a result, the image file group shown in FIG. 6 is classified into 13 groups as shown in FIG. 10, and each group is stored in a folder.

  In this way, if image files are classified into one group exceeding the specified number even after classification by date, classification by time is further performed to make the classification closer to the shooting scene. This makes it easy to manage image files after classification.

  Next, a second embodiment of the image classification program according to the present invention will be described.

  The image classification program according to the second embodiment classifies image files into groups having the same month information, and further includes a group having date information that matches a main event (for example, New Year, Christmas, etc.). It classifies every.

  Note that the image classification program of the present embodiment is also incorporated into the image browsing program in the same manner as the image classification program of the first embodiment, and is provided as a function of the image browsing program. Therefore, only the image classification process will be described here.

  FIG. 11 is a flowchart illustrating a procedure of image file classification processing by the image classification program according to the second embodiment.

  First, a folder to be classified is selected (step S30). As in the case of the image classification program of the first embodiment, the folder is selected on the folder tree display frame.

  Next, the execution of the classification process is instructed to the selected folder. The CPU 12 determines the presence / absence of this instruction (step S31). If the CPU 12 determines that an instruction to execute the classification process has been issued, the CPU 12 executes the classification process for the image file stored in the selected folder.

  The image file is classified based on the date information of each image file. The image file is classified for each month (step S32), and the classified image file is further classified for each event (step S33).

  For example, assume that an image file group as shown in FIG. 12 is stored in a selected folder. When the classification process is executed on the image file group stored in this folder, first, grouping is performed on a monthly basis (step S32). In this case, grouping is performed regardless of year and day. In the example shown in FIG. 12, since there are image files having month information of January, March, May, June, November, and December, January, March, May, June, and November. , It is classified into the group of December.

  Next, classification by event is performed for each month group (step S33). The classification by the event is performed based on the date information. That is, it is classified for each group having event date information. For example, for each group that has date information of events, such as “New Year” for January 1 to January 3, “Hinamatsuri” for March 3, “Children's Day” for May 5, etc. Classify into: As shown in FIG. 13, the date information of the events to be classified is provided as data in the image management program, and the CPU 12 classifies each event based on this data.

  In the example shown in FIG. 12, for example, in the December group, there are image files having date information of 24th, 25th, and 28th, among which image files having date information of 24th and 25th are event “ Since it corresponds to “Christmas”, image files having date information of 24th and 25th are classified.

  On the other hand, since there is no image file having date information corresponding to the event in the June group, classification is not performed in this case.

  In this way, classification by event is performed on a monthly basis for image files classified on a monthly basis. As a result, as shown in FIG. 14, the image file group in the example shown in FIG. 12 includes (1) “DSCF0001” to “DSCF0006” (New Year), (2) “DSCF0007” to “DSCF0012” (Hinamatsuri), ( 3) “DSCF0013” to “DSCF0016” (Children's Day), (4) “DSCF0017” to “DSCF0019” (June), (5) “DSCF0020” to “DSCF0021” (Day of Work Appreciation), (6) It is finally classified into seven groups “DSCF0022” to “DSCF0042” (Christmas) and (7) “DSCF0043” to “DSCF0045” (December).

  Then, a predetermined folder name is assigned to each group of the image files grouped in this way and stored individually in the folder (step S34). At this time, the folder for storing the image file of each group is created in the folder selected as the classification target, and the classified month or event name is given to the folder name. As shown in FIG. 15, a list of classified folders is displayed in the thumbnail display area of the image browsing program displayed on the display device 20.

  As described above, according to the image classification program of the present embodiment, the image file group to be classified is classified by month, and further classified by event within the same month. As a result, the classification can be made close to the scene of image shooting, and the management of the image file after classification becomes easy.

  In this embodiment, the year is separated, the month is classified, and then the event is classified. However, after the year is classified, the month is classified and the event is further classified. Classification may be performed.

  Next, a third embodiment of the image classification program according to the present invention will be described.

  The image classification program according to the third embodiment classifies each area using GPS data included in the image file.

  Note that the image classification program of the present embodiment is also incorporated into the image browsing program in the same manner as the image classification program of the first embodiment, and is provided as a function of the image browsing program. Therefore, only the image classification process will be described here.

  FIG. 16 is a flowchart illustrating a procedure of image file classification processing by the image classification program according to the third embodiment.

  First, a folder to be classified is selected (step S40). As in the case of the image classification program of the first embodiment, the folder is selected on the folder tree display frame.

  Next, the execution of the classification process is instructed to the selected folder. The CPU 12 determines the presence / absence of this instruction (step S41). If the CPU 12 determines that an instruction to execute the classification process has been issued, the CPU 12 executes the classification process for the image file stored in the selected folder.

  The classification of the image files is performed based on GPS information (latitude information and longitude information) included in each image file. That is, in a digital camera having a GPS function and recording image data in the Exif format, GPS information at the time of shooting can be written in the image file, and the image file is classified using this GPS information.

  The classification based on the GPS information is obtained by acquiring GPS information for each image file, collating the acquired GPS data with the area data, and classifying the corresponding area. The area data is a database of place names for a certain range of latitude and longitude, and is preliminarily provided as data by the image management program.

  For example, assume that an image file group as shown in FIG. 17 is stored in a selected folder. When the classification process is executed on the image file group stored in this folder, for example, the image file “2003225-003” has GPS information of 35 degrees 27 minutes north latitude and 139 degrees 38 minutes east longitude. From the regional data, it is classified as “Yokohama”. Also, the image file “2003225-004” has GPS information of 35 degrees 27 minutes north latitude and 139 degrees 38 minutes east longitude, so it is classified as “Yokohama” from the regional data. On the other hand, the image file “20031230-118” is classified as “Kamakura” from the regional data because it has GPS information of 35 degrees 18 minutes north latitude and 139 degrees 33 minutes east longitude.

  In this way, the image files are classified into groups for each same region based on the GPS information included in the image file.

  Note that image files that do not have GPS information are classified into one group as others.

  As described above, when the image file group is classified by region, the image file group in the example shown in FIG. 17 is (1) “2003225-003” to “2003225-011” (Yokohama), (2) “20031230- 118 ”to“ 20031230-126 ”(Kamakura), (3)“ 20031230-212 ”to“ 2003227-224 ”(Enoshima), (4)“ 2003227-300 ”to“ 2003227-304 ”(others) Classified into groups.

  A predetermined folder name is assigned to each group of the image files thus grouped and stored individually in the folder (step S43). At this time, the folder storing the image files of each group is created in the folder selected as the classification target, and the classified region name is given to the folder name. In the thumbnail display area of the image browsing program displayed on the display device 20, a list of classified folders is displayed as shown in FIG.

  Thus, according to the image classification program of the present embodiment, classification is performed for each region based on the GPS information that the image file has. As a result, the classification can be made close to the scene of image shooting, and the management of the image file after classification becomes easy.

  Next, a fourth embodiment of the image classification program according to the present invention will be described.

  The image classification program according to the fourth embodiment classifies image files by year and further classifies them according to shooting information.

  Note that the image classification program of the present embodiment is also incorporated into the image browsing program in the same manner as the image classification program of the first embodiment, and is provided as a function of the image browsing program. Therefore, only the image classification process will be described here.

  As described above, the image classification program according to the present embodiment classifies image files by year and further classifies them according to shooting information. The classification based on the shooting information is performed by using the attached information of the image file recorded in the Exif format.

  As shown in FIG. 19, the Exif format image file can record the attached information in the tag format in the image file header portion. The attached information tag includes information about the version and image data as shown in FIG. Shooting data relating to a shot image such as information relating to the characteristics of the image, information relating to the structure, user information, related file information, information relating to the date and time, information relating to the shooting conditions, information relating to the pointer to the IFD, etc. are recorded in a tag format.

  Here, a manufacturer note, which is a tag related to user information, allows a manufacturer to enter individual information, and a user comment allows a user to write a keyword or comment. Has been.

  Further, as shown in a separate table in FIG. 20, tags related to shooting conditions include exposure time and F number at the time of shooting, exposure program, spectral sensitivity, ISO speed rate, photoelectric conversion function, shutter speed, aperture value, brightness value, exposure. Correction value, Lens minimum F value, Subject distance, Metering method, Light source, Flash, Lens focal length, Flash intensity, Spatial frequency response, Focal plane width resolution, Focal plane height resolution, Focal plane resolution unit, Subject The position, exposure index, sensor method, file source, scene type, CFA pattern, etc. can be recorded.

  Therefore, the classification based on the shooting information is performed based on the attached information of the image file recorded in the Exif format.

  For example, classification based on the presence or absence of strobe light emission, classification based on the type of light source, classification based on subject distance, classification based on subject position, and the like are executed based on the attached information.

  FIG. 21 shows image files classified according to the presence or absence of strobe light emission. In this case, when a folder to be classified is designated and classification execution is instructed, first, the image files in the designated folder are displayed for each year. Then, classification is performed based on the presence or absence of strobe light emission for each classified group. The classified image files are stored in a folder with a predetermined folder name for each group. At this time, each folder is created in the folder selected as the classification target, and a file name that is a combination of the classified year and the strobe ON / OFF is assigned to the folder name (for example, 2003). If there is a strobe light, “2003 strobe ON”).

  FIG. 22 shows image files classified by light source type. In this case, when a folder to be classified is designated and classification execution is instructed, first, the image files in the designated folder are classified by year. Classification into groups is performed, and then classification is performed according to the light source type for each classified group. The classified image files are stored in a folder with a predetermined folder name for each group. For example, a file name combining a classified year and a light source type is given to the folder name (for example, “2002 fluorescent lamp” in the case of the 2002 light source type “fluorescent lamp”).

  As described above, according to the image classification program of the present embodiment, the image file is classified for each year and further classified based on the photographing information of the image file. As a result, the classification can be made close to the scene of image shooting, and the management of the image file after classification becomes easy.

  Note that as shooting information used for classification, any information of the attached information attached to the image file in the Exif format may be used, or the user may be able to select. For example, as shown in FIG. 23, it is configured such that selectable shooting information is displayed in a dialog box that supports execution of an image file, and the user can select shooting information to be classified.

  Even in the case of an image file recorded in a format other than Exif, if shooting information is attached to the image file, classification may be performed using the shooting information.

  In the above-described series of embodiments, when specifying an image file to be classified, a folder in which the image file is stored is selected. However, classification is performed by individually specifying the file. You may make it do.

  Further, when there is a function of automatically importing image files from the digital camera or memory card connected to the personal computer 10 to the hard disk drive 16, the image files may be automatically classified when they are imported to the hard disk drive 16. Good.

  In the series of embodiments described above, the case where the image classification program according to the present invention is used as application software for a personal computer has been described as an example. However, the image classification program may be used as a program executed on a digital camera.

  Furthermore, in the series of embodiments described above, the finally classified image files are stored in folders for each group, but a copy of the classified image files may be stored in each folder. In this case, the image file before classification is stored in the folder designated as the classification target as it is.

  Further, shortcut files of classified image files may be stored in each folder. Also in this case, the image file before classification is stored as it is in the folder designated as the classification target. By storing the shortcut file in each folder in this way, the total file size required can be reduced as compared with the case where the classified image file is copied.

Block diagram showing hardware configuration of PC The figure which shows the main window screen of the image browsing program Flow chart showing the procedure of image file classification processing The figure which shows the example of a display of the window screen at the time of selection of the folder made into a classification object The figure which shows the example of a display of the window screen at the time of execution instruction of image file classification Figure showing an example of image files to be classified Explanatory drawing of the image classification method in the image classification program of 1st Embodiment The figure which shows the example of a display of the window screen after classification processing execution Flow chart showing the procedure of image file classification processing Illustration of image file classification method Flow chart showing the procedure of image file classification processing Illustration of image file classification method Figure showing date information data of events to be classified Illustration of image file classification results Showing a display example of the window screen after execution of similar processing Flow chart showing the procedure of image file classification processing Illustration of image file classification method Showing a display example of the window screen after execution of similar processing Diagram of image file recorded in Exif format Explanatory drawing of attached information attached to an image file recorded in Exif format Illustration of image file classification method Illustration of image file classification method The figure which shows the example of a display of the window screen at the time of execution instruction of image file classification

Explanation of symbols

  DESCRIPTION OF SYMBOLS 10 ... Personal computer, 12 ... Central processing unit (CPU), 14 ... RAM, 16 ... Hard disk drive (HDD), 18 ... CD-ROM drive, 20 ... Display device, 22 ... Input device, 24 ... Memory card, 26 ... Memory Card slot 28 ... Digital camera 30 ... Input / output terminal 32 ... Modem 34 ... Bus

Claims (6)

An image classification program for classifying image files with file names combining free characters and file numbers,
Obtaining a plurality of image files to be classified;
Classifying the acquired multiple image files into groups of the same free character;
Further classifying image files classified into groups of the same free character into groups of consecutive file numbers;
Further classifying the image files classified for each group of consecutive file numbers into groups having the same date information;
Assigning a specific folder name to each final classified group and storing the image file in the folder;
Classification program for causing a computer to execute.   The method according to claim 1, further comprising the step of classifying each group having the same time information when the number of image files of the group having the same date information exceeds a preset number of files. Image classification program. An image classification program for classifying image files,
Obtaining a plurality of image files to be classified;
Classifying the acquired plurality of image files into groups having the same year information;
Further classifying the image files classified for each group having the same year information for each group having specific shooting information;
Assigning a specific folder name to each final classified group and storing the image file in the folder;
Classification program for causing a computer to execute.   The image classification program according to claim 3, wherein the specific shooting information is presence / absence of strobe light emission, subject distance, or light source type. An image classification program for classifying image files,
Obtaining a plurality of image files to be classified;
Classifying the acquired plurality of image files into groups having the same month information;
If there is an image file having date information of a preset event among image files classified for each group having the same month information, the step of classifying for each group having the date information;
Assigning a specific folder name to each final classified group and storing the image file in the folder;
Classification program for causing a computer to execute. An image classification program for classifying image files,
Obtaining a plurality of image files to be classified;
Classifying the acquired plurality of image files into groups each having a predetermined range of latitude and longitude information;
Assigning a specific folder name to each classified group and storing the image file in the folder;
Classification program for causing a computer to execute.

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