JP4861123B2 - Image management apparatus, camera, image management method, program - Google Patents

Description

The present invention relates to an image management technique that makes it easy to search for photographic images by classifying image groups.

Due to the increase in capacity and price of recording media, a large number of images can be stored in a camera or the like. Since a large number of images can be stored, it takes time to search for a specific image. It takes a long time to search, which is a big problem for usability of cameras and players. Thus, many proposals have been made to shorten the search time.

  As one method, there is a method for displaying and managing a large number of images divided into several groups. This is because if the images are displayed properly in groups, the number of images to be searched is considerably reduced, and the target image can be easily searched.

  For example, in thumbnail image display, an image processing apparatus has been proposed that facilitates searching by inserting a headline image between thumbnail images (Patent Document 1).

  There has also been proposed an image search apparatus that automatically performs grouping according to shooting time. In this image retrieval apparatus, images are grouped by determining the shooting frequency from the shooting date and time (Patent Document 2). Further, as an example of thumbnail image display, an image processing apparatus has been proposed in which an expanded display that displays all group images and a closed display that displays only representative images are selected and displayed for images belonging to the group ( Patent Document 3).

Furthermore, an image input device has also been proposed that makes it easy to select an image file corresponding to the print size by displaying the color of the frame of each thumbnail image in a color according to the roughness of the resolution (Patent Document). 4).
JP 2000-217055 A JP 2003-141130 A JP 2000-041209 A JP 2001-036843 A

  A general user operation example regarding image capturing and image playback will be described with reference to the flowchart of FIG. The flowchart in FIG. 16A is a procedure of the user's photographing operation. Since shooting is performed when there is an event, if there is any event for the user (YES in step S201), shooting is performed (step S202). After shooting, a print reservation operation can be performed on the shot image. If a print reservation operation is performed (YES in step S203), the designation is performed (step S204). However, in many cases, there are few users who prefer such a troublesome operation for every shooting. In the first place, it is common to decide which image to print after looking at the entire captured image, such as when traveling, and if you specify print for each shooting, it is manageable how many sheets to print Because it becomes difficult, few users have these habits.

  The flowchart in FIG. 16B shows a user operation procedure in a playback scene. Usually, the camera is not used for a while after shooting, and even if there is an image that you want to see, it is not clear how to remember, and it is often unclear how to search. Therefore, users often come up with the idea of sorting and organizing only after coming here. When the classification operation is selected (YES in step S211), the screen is switched to a classification screen (for example, as introduced in Patent Document 1 or 3 above), and image classification is designated in accordance with the instruction (step S212).

  At the time of image search, a list display screen is used (step S213). When the target image is found during the list display, the image is selected (step S214). This is because each image on the list display is difficult to see on the small display screen of the camera, and it is possible to surely determine whether it is necessary or not by enlarging the images. When an enlargement instruction is given for the selected image (YES in step S215), the image is enlarged and displayed (step S216).

If it is determined that the image is not good, the unnecessary image is deleted or deleted. When a deletion instruction is given (step S217 YES), the corresponding image is deleted (step S218). If there is no instruction for deletion, the list is again reduced and displayed (step S219). Further, if there is an end instruction (YES in step S220), the end process is performed. If there is no end instruction (NO in step S220), the state returns to a state where classification is possible (step S211).
In the conventional series of operations described above, the images are grouped and displayed. However, when the number of images increases, it is difficult to know which image is where, and this tends to cause confusion. Therefore, there is a demand for a display device that makes it easier to search for images than the conventional list display. That is, there is a demand for an image management apparatus that appropriately manages the number of classified images and manages the classified images efficiently.

  In view of the above problems, the present invention provides an image management apparatus that facilitates image search by optimizing the number of classified images or efficiently displaying classified images, a camera equipped with the image management apparatus, Such an image management method and program are provided.

In order to achieve the above object, an image management apparatus according to a first invention includes an image classification unit that classifies images according to the theme of the photographed image and the photographing date and time, and the classified content of the classified image. A display control unit for displaying thumbnails together with the classification marks to be displayed. Alternatively, the classified thumbnail image is hidden and displayed instead as a representative mark representing the classification, and is switched according to an instruction.When the image classification unit classifies the image according to the shooting date and time, Assume that images with a certain shooting time are included in the same time range, and set this time width so that the number of images belonging to one category does not exceed a certain number It is to shall.

  According to a second aspect of the present invention, there is provided a camera having an image classification unit for classifying images on the basis of a shooting date and time, wherein the image classification unit determines a date and time of a captured image and a date and time of an image captured before that. In comparison, it is determined that the shooting date interval is within a certain period, and if it is within a certain period, the number of images included in the previous image classification is further determined, and the number of included images is constant. If the number is less than the number, the captured image is registered in the previous image classification, and if the number of the included images is equal to or greater than a certain number, the captured image is registered in a new classification different from the previous image classification. It is.

According to the present invention, an image management apparatus that facilitates image search by optimizing the number of classified images or efficiently displaying classified images, a camera equipped with the image management apparatus, and such an image Management methods and programs can be provided.

The best mode for carrying out the present invention will be described below with reference to the drawings.
(First embodiment)
The first embodiment will be described with reference to FIGS. In the first embodiment, captured images are classified according to a theme, and the classified images are displayed as specific thumbnail images.

  FIG. 1 is a block diagram of a camera 1 equipped with an image management apparatus to which the present invention is applied. The image management apparatus mainly includes an image determination unit, an image processing unit, a display control unit, an MPU, and a ROM, which will be described later.

  The camera 1 includes a photographing lens unit 2, an AF control unit 2a, a diaphragm unit 3, a diaphragm control unit 3a, an image sensor 4, and an analog front end (hereinafter abbreviated as AFE) unit 5.

  The taking lens unit 2 forms an image of the incident subject 20 on the image sensor 4. The taking lens unit 2 has a focus lens inside. The AF (autofocus) control unit 2a detects the focus position, drives the focus lens, and moves the focus lens to the focus position. The AF control unit 2a detects the in-focus position (focus position) from the contrast signal peak of the captured image by a method called so-called hill-climbing detection.

  In or near the photographic lens unit 2, a diaphragm unit 3 that provides a shutter or diaphragm effect is provided. The diaphragm unit 3 opens to a predetermined aperture at the time of photographing, and closes to end the exposure when the exposure ends. The aperture control unit 3a drives the aperture unit 3 to set the aperture diameter. By changing the aperture, the depth of field of the lens changes, so you can adjust the blurring of the background, etc. to switch the expression, such as floating the subject or drawing the background firmly Can do.

  The image pickup device 4 is a CCD, a CMOS sensor, or the like including a large number of light receiving surfaces (pixels). The image sensor 4 receives an image from the subject 20 via the photographing lens unit 2 and converts it into an image signal.

  The analog front end (AFE) unit 5 includes AD (analog / digital conversion) means, and converts a signal from the image sensor 4 into a digital signal. The AFE unit 5 performs various processes on the image signal output from the image sensor 4. The AFE unit 5 is also provided with a function of reading several pixels of the image sensor 4 in a lump. For example, when the signal level of each pixel is small, such as 4 pixels (2 × 2) and 9 pixels (3 × 3), several pixel signals can be added to improve the S / N. Sensitivity can be increased by such an operation. In this way, S / N can be improved by adding and using several pixel signals of the same color of the image sensor.

  Such an operation can increase sensitivity. As described above, when the sensitivity is increased, it is possible to devise in photographing such as increasing the shutter speed. When the shutter speed is high, it is possible to shoot as if the moving subject is stopped. For cameras that allow the user to switch the shutter speed and control the exposure appropriately by controlling the aperture and sensitivity, if the shutter speed is generally slowed down, for example, when shooting a river flow, the water flow is like a thread. This makes it possible to depict images that have been extended. If you increase the shutter speed, you can capture the same river flow, capture the moment, and make it possible to reproduce the moment when the splashes rise and the state of ripples. Even in sports photos, if the shutter speed is increased, the movement of the subject can be stopped, and the facial expression can be clearly captured.

  The AFE unit 5 also has a function of selecting image signals output from the image sensor 4 and can extract a limited range of image data from all light receiving surfaces. If an image of only a predetermined area is recorded by this control, an effect similar to so-called trimming can be obtained.

  The camera 1 is provided with an image processing unit 6 and an image determination unit 17. The image processing unit 6 corrects the color, gradation, and sharpness of the input signal. The image processing unit 6 includes resizing means for processing the signal from the image sensor 4 into a size that can be displayed on the display unit so that the live image can be displayed on the display unit in real time. By this function, an image incident on the image sensor can be confirmed prior to shooting, and the timing and photo opportunity at the time of shooting can be determined while viewing this. The image processing unit 6 is also provided with a sensitizing unit 6a that automatically increases the ISO sensitivity for a dark subject.

  The image determination unit 17 is for determining a subject and a shooting theme shot by analyzing image data. The image determination unit 17 includes a color determination unit 17a, a contrast determination unit 17b, and a face detection unit 17c. The color determination unit 17a determines a color component included in the image information. The contrast determination unit 17b determines the contrast of the image signal. The contrast is also used for autofocus control of the AF control unit 2a. The distance of the subject, the distance of the background, and the like can also be determined based on the information on the lens position at the time of focusing. The face detection unit 17c examines the feature of the image and detects whether or not a face exists on the screen. A theme determination unit 14a described later determines the theme based on the result of the image determination unit 17.

  Further, the camera 1 is provided with a compression / expansion unit 7, a recording / reproducing unit 8, a recording medium 9, an input / output unit 10, a display control unit 11, and a display unit 12. The compression / decompression unit 7 compresses the signal output from the image processing unit 6 during shooting. The compression / decompression unit 7 includes MPEG (Moving Picture Experts Group) 4 and H.264. A still image compression unit S 7b such as a moving image compression unit M 7a including a compression core unit such as H.264 and a JPEG (Joint Photographic Experts Group) core unit is provided. The recording / reproducing unit 8 records the image signal compressed as described above on the recording medium 9. The recording medium 9 is a storage recording medium that can be attached to and detached from the camera.

  The recording / playback unit 8 records the classification data of the image on the recording medium 9 as a “classification file”. The classification data is classification information based on the shooting theme of each image determined by the theme determination unit 14a, or classification information based on the shooting date and time classified by the date and time classification unit described later. The classification based on the shooting date will be described in detail in the second embodiment. The recording file 9 stores a classification file 9a together with image data.

  The display unit 12 includes, for example, a liquid crystal or an organic EL, and displays a monitor image at the time of shooting, and displays a recorded image that has been subjected to expansion processing at the time of reproduction. The display control unit 11 controls display on the display unit 12. The display control unit 11 has a multi-control unit 11a. The multi-control unit 11a displays a thumbnail image on the display unit 12.

  At the time of reproduction, the compression / decompression unit 7 decompresses the compressed data recorded on the recording medium 9, and the image processing unit 6 further performs conversion processing into an image suitable for display. The converted image is viewed as a reproduced image on the display unit 12 via the display control unit 11. The input / output unit 10 relays the exchange of image data and other data with an external person 30 via a network. It is also possible to input the image data 31 from the outside.

  The camera 1 includes an auxiliary light emitting unit 13, an MPU 14, a ROM 16, a release switch 15a, a mode switch 15b, and another switch 15c. The auxiliary light emitting unit 13 includes a white LED and a Xe discharge arc tube, and the amount of light can be controlled by the amount of current flowing. Depending on the situation, the subject 20 is irradiated with light to prevent lack of brightness and uneven brightness.

  The MPU 14 is a control unit that controls the entire camera. The release switch 15a, the mode switch 15b, the other switch 15c, and the ROM 16 are connected to the MPU 14. Each switch 15a-15c detects a user's operation, and notifies the result to MPU14 which is a calculation control means which consists of a microcontroller. The MPU 14 switches the operation according to the operation of these switches. The MPU 14 functions as a shooting control unit that controls the AF control unit 2a, the aperture control unit 3a, and the like during shooting.

  The ROM 16 is a non-volatile and recordable memory, and is composed of, for example, a flash ROM, and stores a control program for performing control processing of the camera 1. The MPU 14 reads a program from the ROM 16 and executes it.

  The MPU 14 includes a theme determination unit 14a, a date / time classification unit 14b, and an image classification unit 14d as functions of control processing. The theme determination unit 14a determines the theme name of the captured image (subject) from the results of the image determination unit 17 including the color determination unit 17a, the contrast determination unit 17b, and the face detection unit 17c described above. The theme name is, for example, portrait, landscape, pet or the like.

  The theme determination unit 14a also uses shooting conditions such as a subject or background focus position, zoom position, shooting time, exposure control parameters, distance information, and color information when determining the theme. This is because various information about the subject can be obtained depending on the distance of the subject to be photographed. This is because, for example, macro photography does not take pictures of landscapes. By these, various classifications are possible.

  FIG. 2 is a diagram illustrating an appearance of a camera held by a photographer at the time of photographing. Contrast information obtained from the subject when the camera 1 is held at the time of shooting (observation with the display unit 12 while reproducing the output of the image sensor and pointing the release button 15a with a finger toward the timing and composition) Information on a target that the user 20 wants to shoot is obtained based on color, background, focus information, and the like. The image classification unit 14d classifies images based on the results of the theme determination unit 14a and / or the date / time classification unit 14b. The result of this classification is recorded on the medium 9 as the classification file 9a.

  The MPU 14 has a built-in clock unit 14c. The photographing time measured by the clock unit 14c is very important, and the photographing time and photographing frequency are important factors for determining the theme of the photographing (for example, a night view for night scenery). The date and time classification unit 14b classifies the captured image from the measured shooting date and time.

  FIG. 3 is a flowchart for explaining the procedure of image theme classification processing. The left side is a flowchart of theme classification processing, and the right side is a flowchart of display processing according to classification. This process is a process of performing theme classification so that the numbers are retroactively started from the selected images for a group of thumbnail images displayed on the screen. The theme classification process is performed by an image management apparatus (mainly MPU 14, theme determination unit 14a, image determination unit 17, image classification unit 14d, display control unit 11, etc.).

  Here, it is assumed that the camera 1 is set to the theme classification process in the playback mode, and the thumbnail image is displayed on the display unit 12. FIG. 7 is a diagram illustrating a screen that transitions according to the theme classification process. The display unit 12 displays a total of 16 thumbnail images, four vertically and horizontally. The numbers in each area are image numbers assigned based on the order of shooting date and time. The lower the number, the older the shooting date and time. FIG. 7A-1 shows the first screen where thumbnail images No. 15 to No. 30 are displayed.

  First, the target image p is selected according to a user instruction on the screen (step S11). Assume that the image (No 30) in the lower right corner is selected (FIG. 7A-1). Here, an example of an image selection operation will be briefly described. While viewing the display unit 12 on the back of the camera 1, the user operates the cross-shaped key, which is one of the operation keys, to select it.

  Then, the theme of the selected target image p is determined (step S12). Move on to the subroutine of FIG. FIG. 4 is a flowchart for explaining a subroutine for theme determination. First, the face detection unit 17c determines whether there is a face in the detection target image (step S31). FIG. 5 is a diagram for explaining the principle of face detection by the face detection unit 17c. FIG. 5A shows a template corresponding to the shadow of a human face. Three examples with different sizes are shown as templates (a-1, a-2, a-3). FIG. 5B shows the entire detected image. On this image, the image is moved within the screen while changing the size of the template, and it is determined whether there is a portion that matches the contrast of the template. If there is a place where the degree of coincidence with the template is high, it is determined that there is a face there. Then, the detected part is specified as a face region f in the image (FIG. 5C).

  When a face is included (step S31 YES), the size of the face in the image is determined (step S32). If the face is large (YES in step S32), the theme is determined to be a portrait (step S34). If the face is small (step S32 NO), the theme is determined to be a snap (step S33). In a scene that does not include a face (NO in step S31), when the subject distance is a long distance (YES in step S35), the theme is determined to be a landscape image from the distance based on the focus result (AF) (step S41). . If the subject distance is close (YES in step S36), it is determined that the image is a flower image (step S38) or an accessory image (step S39) by color (step S37). Otherwise, it is determined as a pet image (step S40).

  Of course, the color of a landscape or the like may also be determined. For example, the sky or the sea may be determined depending on where there is a blue object. FIG. 6 shows an example in which images (portraits) in which the subject is only a face are collected.

  Returning to FIG. An image that is subject to theme comparison with the target image p is called a comparison image q. In this example, the comparison image q is retroactively checked one by one along the image number. First, it is checked whether there is an image before the target image p (step S13). Here, since the image of No. 29 exists, first, No. 29, which is the previous image, is used as the comparison image q, and the theme of this image is determined. If there is no previous numbered image, the process jumps to step S23.

  It is determined whether the comparison image q (No. 29) is an image that has already been subjected to theme determination (step S14). This can be done by referring to the classification file 9a and searching for the theme name No. 29. If the comparison image q is an image that has not been subjected to theme determination (step S14 NO), theme determination is performed (step S15). The subroutine of FIG. 4 is executed again to determine the theme of the comparative image q. If the image has already been determined, the theme name is read from the theme file 9a.

  Then, the subject of the target image p and the obtained comparison image q is compared (step S16). If it is determined that the theme is the same (step S17 YES), the same classification is made (step S18). Then, the frame color of the thumbnail of the previous image is changed to the same frame color as that of the target image (step S19). The screen display is changed as shown in FIG. Here, the frame color is a predetermined frame color for each theme. The theme name of No. 30 is recorded in the classification file 9a. If the theme name No. 29 is not recorded, it is recorded.

  Next, in order to make a theme determination for the previous image, it is determined whether there is another image before the current comparison image q (step S21). If no image exists, the process proceeds to step S23. Here, since the No. 28 image exists, the comparison image q is changed to the No. 28 image (step S22), and the process returns to step S14. The theme determination or the like (step S14 or the like) is repeated for the image No. 28 which is a new comparison image. Then, the theme determination of the displayed image No. 15 is performed, and when this is completed, there is no comparison image, and the process proceeds to step S23.

  At this time, it is assumed that No. 18, 20, 23, and 29 are determined to have No. 30 as the same theme. As shown in FIG. 7A-3, the frame colors of these five images are displayed in the same color.

  Next, the target image is changed. The next target image p is an image having a lower number than the previous target image and is not determined to be the same theme as the previous target image. The presence / absence of the next target image p is determined (step S23). Here, the image of No. 28 becomes the new target image p. The target image p is changed to No28 (step S24). The relationship is as shown in FIG.

  Then, returning to step S12, the theme determination is performed in the same manner as the previous time, and the above-described series of processing is performed using No27 as the comparison image q (from step S12 to step S20). This is repeated up to the image No. 15. As a result, it is assumed that Nos. 28, 27, and 26 are determined to be the same theme. Then, a screen as shown in FIG. 7B-2 is displayed. The frame colors of the three images are displayed in the same color. In this figure, for the sake of clarity, the display of five images of the same classification as No. 18 is omitted.

  Further, the target image p is changed again (this time, No25 becomes a new target image p), and this is repeated for all the images displayed as thumbnails, so that the theme classification processing of the displayed image is performed. Is done. When there is no more target image p (step S23 YES), the classification is terminated.

  Next, the display of the themes classified images will be described with reference to FIGS. The display is switched automatically or according to a user instruction after the classification process according to the flowchart. It is determined whether there is an image classified into the same theme (step S25). If all the images are different themes (step S25 NO), the process ends here. If there is an image classified into the same theme (YES in step S25), the image is classified and displayed for each theme as follows, and a message to that effect is displayed at the beginning or end of each theme.

  Since the number of thumbnail images that can be displayed is limited, not all images belonging to the theme can be displayed at the same time. In other words, in the above-described theme classification, it has been explained that the theme classification processing is performed only for the images displayed in thumbnails. However, it is natural that the classification processing is executed for more images, and as a result, the number of images belonging to one theme is one. This is because it is easily estimated that there is a possibility of exceeding the number of thumbnail display times (for example, 17 or more). Therefore, a dedicated image for clarifying the division of the theme image is displayed.

  First, it is determined whether the first image of the theme is displayed on the screen (step S26). This is because only a small number of images can be displayed on the screen at one time. When the first image of the theme (the oldest shooting date and time) is displayed on the screen, the image can be displayed at the top (YES in step S26), and the theme start mark is inserted and displayed at the top (step S27).

  FIG. 8A is a display example of the theme classification screen. For example, when No. 18, 20, 23, 29, and 30 are “portrait” images, a “portrait” theme start mark Is1 is displayed at the top thereof. Further, when No. 26, 27, and 28 are “landscape” images, a “landscape” theme start mark Is2 is displayed at the top thereof. Further, No. 15 and later are set as “pet” images, and a “pet” theme start mark Is3 is displayed at the top thereof.

  The theme start marks Is1, Is2, and Is3 are images having the same size as the thumbnail images. 8B-1 and 8B-2 are enlarged views of the theme start marks Is1 and Is2. In the theme start marks Is1 and Is2, an image in which the theme is symbolized and the theme name are displayed inside. In portraits, people's faces are displayed, and in landscapes, mountains are displayed as symbols. Further, the theme start mark may be displayed simply by omitting the symbolized image and theme name as in Is3. An example of the color scheme of the thumbnail image frame to be displayed is shown in FIG.

  If the first image of the theme (the oldest shooting date / time) cannot be displayed on the screen (NO in step S26), it is determined whether the last image of the theme (the newest shooting date / time) is displayed ( Step S28). When the last image can be displayed (YES in step S28), the theme end mark Ie is displayed at the last (step S29). FIG. 8C shows a display example of the theme end mark Ie. The direction of the arrow is opposite to that of the theme start mark Is. Although this Ie is simply displayed, it may naturally be displayed with a symbol mark or theme name as shown in FIG. 8 (B-1).

  9 and 10 are diagrams for explaining the display change of the theme classification screen of FIG. The thumbnail display as described with reference to FIGS. 7 and 8 is inconvenient in that the image is small and is not suitable for confirming the detailed contents, and the number of images that can be displayed in a batch is limited. Therefore, the theme start mark and the theme end mark are also used for the display representative of the entire image belonging to the theme, and the theme classification display is made more efficient.

  FIG. 9 is a flowchart illustrating a processing procedure for changing the display. FIG. 10 is a diagram showing a change of the theme classification screen. In FIG. 9, it is determined whether the theme start mark Is or the theme end mark Ie has been selected by the user (step S51). These are Is1 and Is2 in FIG. When the theme start mark is selected (YES in step S51), it is determined whether the selected theme start mark is currently displayed as a theme separator or as a representative of the theme (step S52).

  The delimiter display (also referred to as delimiter mark) is a display of Is1 and Is2 in FIG. The representative display (also referred to as a representative mark) is a display indicated by Is4 and Is5 in FIG. In the representative displays Is4 and Is5, a broken line frame is added to the separators Is1 and Is2. The images (Nos. 18, 20, 23, 29, and 30) belonging to the portrait are all displayed in FIG. 10A and are not displayed in FIG. This broken line frame indicates that the theme image is hidden.

  Therefore, when Is1 in FIG. 10 (A) is selected (YES in step S52), the theme start mark is switched to the representative display Is4 as shown in FIG. 10 (B), and images belonging to the theme are hidden (step S54). ). Conversely, when Is4 in FIG. 10B is selected (NO in step S52), all the theme images are displayed as in Is1 in FIG. 10A (step S53). In the above description, the theme start mark has been described, but the theme end mark is similarly switched between the separator display and the representative display.

  Next, it is determined whether an image is selected by the user (step S55). When one of the displayed images is selected (step S55 YES), if the selected image is not the currently enlarged image (step S56 NO), it is enlarged and displayed (step S58). For example, when No. 26 and No. 27 are selected in FIG. 10 (A), No. 26 and No. 27 are enlarged and displayed as shown in FIG. 10 (C). Conversely, if the selected image is an enlarged image, it is reduced and displayed (step S57). That is, when No. 26 and No. 27 enlarged in FIG. 10C are selected, the size is returned to a small size as shown in FIG.

  Further, the presence / absence of a scroll operation using the cross key is determined (step S59), and if the scroll operation is performed, the screen is switched and displayed according to the operation direction (step S60).

  As described above, according to the first embodiment, it is possible to display images of the same theme in an easy-to-understand manner on a list, and to attach a cover page or a tail image attached thereto. Then, since a mark indicating a break is inserted and displayed at the beginning or end of the theme on the thumbnail screen, the break of the theme classification can be easily understood. Further, if the theme mark is displayed as a representative mark, images belonging to the theme can be hidden, so that even if the display unit 12 is small, the theme search is facilitated. It makes it easier for users to find where and what images are.

(Second Embodiment)
The second embodiment will be described with reference to FIGS. The second embodiment is an invention that classifies captured images based on the shooting date and time. Since the image management apparatus and the camera applied to the present embodiment have the same configuration as that of the first embodiment, illustration is omitted.

  FIG. 11 is a flowchart illustrating a procedure for classifying an image according to the shooting date and time. The date and time classification process is performed by an image management apparatus (mainly the MPU 14, the date and time classification unit 14b, and the image classification unit 14d). This example is a process of classifying images in order of shooting date and time while adjusting the time width (also referred to as date / time difference T) so that the number of images in one group does not become too large (for example, 20).

  First, the date difference T is set to one week (step S61). Next, a counter n indicating the number of images in the group is set to 1 (step S62). The shooting date / time of the target image is read (step S63). Specifically, the corresponding image file is read from the recording medium 9, and the shooting date and time is read from the incidental information area of the image file. In the following description, the target image is the last image taken.

  It is confirmed whether there is an image with a number before the target image (step S64). If there is no previous image, there is only one image, so the classification process ends. If the previous image exists, the shooting date and time of the previous image is read (step S65). This is the same as step S63. Then, the shooting date / time of the target image is compared with the shooting date / time of the previous image (step S66).

  It is determined whether the date and time difference is within the date and time difference T set in step 61 (step S67). Initially, T = 1 week. If the date difference is within T (YES in step S67), it is determined that the image has been added to the classification, the counter n is incremented by 1 (step S68), and the process returns to step 64. Further, the presence / absence of the previous image is determined (step S64), the shooting date / time is read (step S65), and it is determined whether the date / time difference is within T (step S67).

  When the above is repeated and the date difference T is exceeded, it is determined whether the number of images up to here from the counter n value is less than a predetermined value. It is determined whether the number of images in one group is within 20 (step S69). If the number of images exceeds 20 (YES in step S69), it is determined that the number of images in one category is too large, the date difference T that is a criterion for creating the category is shortened (step S70), and the classification is performed again. The date difference T is set to “2 days”, for example, and the process returns to step 62. Then, the loop from step S62 to step S68 is circulated again.

  Repeat until the number of images is 20 or less. If the number of images is within 20, the process proceeds to step S71. In this step, the case where the number of sheets is small is checked. It is determined whether the number of images is one (step S71). If the number of images is one, it is determined that the number is too small (YES in step S72), and the date difference T is lengthened (step S72). For example, if there is only one image in T = 1 week, T is changed to January and the process returns to step 62. Then, the loop from step S62 to step S68 is circulated again.

  If the number of images falls within the range of 2 to 20, it is determined that one class is appropriate and this is determined as one class (step S73). This is recorded in the classification file 9a. Then, for the next classification, the target image in step S63 is changed (step S74). The next image after the last image in the same classification becomes a new target image.

  FIG. 12 is a diagram for specifically explaining the image classification processing of FIG. 11 with an image sequence. The entire image recorded on the recording medium 9 is shown as an image sequence in the order of image numbers. No1 is the first captured image and No80 is the last captured image. The display of numbers is omitted as appropriate.

  As shown in FIG. 12A-1, it is initially checked whether the target image is No80, and is an image shot within one week in order from No79 with respect to No80. Here, 16 images up to No. 65 are taken within one week from the shooting date and time of No. 80. Since the number of images is 2 or more and 20 or less, it is accepted as one classification, so this group is determined as one classification and recorded in the classification file 9a.

  Then, the new target image is set as No. 64, and the number of images within one week before No. 63 is checked. Here, it is assumed that 6 sheets up to No. 59 are within one week. Since this also passes, this is recorded as a 2nd group (FIG. 12 (A-2)).

  Conversely, as shown in FIG. 12 (B-1), it is assumed that images with a date difference T within one week with respect to the target image No80 are No55 and the number of images is 26. Since there are 20 sheets or more, the date difference T is reset to 2 days and the classification operation is performed again. Here, suppose that it became 11 sheets to No70 (B-2). Since it passes, register as a classification. It should be noted that even if an independent image is at the level of several or ten, it is not felt that it is too much, so it may be a single independent image without creating a set.

  FIG. 13 is a flowchart for explaining processing for performing the date and time classification at the time of shooting. In FIG. 12, the classification process is collectively performed at the time of reproduction after shooting. However, in this example, the process is to classify the shot image immediately after shooting. Which timing is used is an arbitrary design matter.

  First, photographing is performed based on the release instruction of the photographer (step S81). Date and time determination at the time of shooting is performed (step S82). The shooting date and time is determined by the clock unit 14 c in the MPU 14. It is determined whether one previous image exists (step S83). If the previous image exists (YES in step S83), the date and time of the previous image is determined (step S84). The date and time can be read from the incidental information of the image file. The difference in shooting date and time with the previous image is compared (step S85), and the classification process is changed as follows.

  First, it is determined whether the date difference is one week or more (step S86). If the date difference is one week or more (step S86 YES), the captured image (target image) is not set to the same classification as the previous image, but is set as the first (first) image of the new classification (step S87). ). This is because the date and time interval is too large for the same classification. In addition, the previous image is set as the end image of the classification to which the previous image belongs (step S88).

  On the other hand, if the date difference is within one week (NO in step S86) and more than one day (YES in step S89), it is determined whether the number of images in the date and time classification up to the previous time is five or more (step S90). If the number is 5 or more (YES in step S90), it is determined that the captured image should be newly classified, and the process proceeds to step 87. Since steps 87 and 88 have been described above, a description thereof will be omitted. On the other hand, if it is less than 5 (NO in step S90), it is set to the same date and time classification as the previous image (step S91).

  If the date difference is within one day (NO in step S89) and more than one hour (YES in step S92), it is determined whether the number of images in the previous classification is 10 or more (step S93). If there are 10 or more images (YES in step S93), it is determined that the captured image should be newly classified, and the process proceeds to step 87. Since steps 87 and 88 have been described above, a description thereof will be omitted. On the other hand, if the number is less than 10 (NO in step S93), the same date and time classification as the previous image is set (step S91). Here, if there is no date difference (even if it is not the next day), the date difference is determined by 1 hour. This is because classification is possible when the user moves to another place during a trip or the like. Also, if 10 or more images are associated with the same classification, it may be considered that a large number of images have already been collected.

  If the date difference is within 1 hour (NO in step S92), it is determined whether the number of images in the previous classification is 20 or more (step S94). If there are 20 or more images (YES in step S94), it is determined that the photographed image should be newly classified, and the process proceeds to step 87. Since steps 87 and 88 have been described above, a description thereof will be omitted. If it is less than 20 sheets (step S94 NO), the same date and time classification as the previous image is set (step S91).

  This is because, even if images of a series of events have not been passed for an hour or more and 20 images have already been collected, they will not be organized if they are packed more. In addition, a large number of images can be obtained for each event in an athletic meet scene that repeats continuous shooting or the like, so the number of determinations is 20 times that of step S93.

In addition, here, only the time difference and the number of images were used as the criteria for judgment. Naturally, the above-mentioned classification for each switching parameter at the time of camera shooting, GPS (Global Positioning System), etc. are installed, and location information is taken into account. Image classification may be performed.
In this case, the date / time difference determination may be “location difference determination”, or classification according to the difference is performed as in “zoom position difference determination”.

  As explained above, every time a shot is taken, the relevance with the previous image is judged and a set of images (group or group) is formed. Thus, it is possible to quickly perform a search during playback. In addition, if the images are sorted in order at the timing of shooting, a general set can be created without any special effort during playback. In addition, a device was devised to optimize the number of images forming a group or set and the method of classification. When the time difference is long, we try not to add extra if there are a lot of previous images, and when there are too many images, the time difference judgment is made stricter, and when there are too few images, the same set is used. For this purpose, the time difference for determination is made longer so that the number of images is appropriate. Also, it is possible to prevent the number of single images from increasing too much and increasing the number of unclassifiable images. Even when the number of images is small, if a predetermined time has elapsed, it is not forced to be combined with other images.

(Third embodiment)
A third embodiment will be described with reference to FIGS. 14 to 15. In the third embodiment, the images classified based on the shooting date and time in the second embodiment are displayed as thumbnail images according to the classification. Since the image management apparatus and the camera applied to the present embodiment have the same configuration as that of the first embodiment, illustration is omitted.

  FIG. 14A is a bar graph showing the shooting date / time distribution of images stored in the recording medium 9a. The shooting date and time are set on the horizontal axis, the number of images is set on the vertical axis, and the lower date and time indicate the date.

  FIG. 5B shows an example in which the images in (A) are classified by day and displayed as thumbnails. Images of the same classification (same day shooting) are displayed in the same frame color (or pattern). No. 15 to No. 21 are taken on 8/10 (August 10), No. 22 to No. 26 are taken on 8/11, No. 27 to No. 29 are taken on 8/12, and No. 30 is taken on 8/13. Since the frame color of the images on the same shooting date is the same color, the shooting date can be easily switched and the image search becomes easy. FIG. 6C is an example in which the images No. 20 and No. 21 in FIG. FIG. 4D is an example in which the frame of the thumbnail image is displayed separately from the solid line and the broken line as another example for distinguishing the classification.

  FIG. 15 shows an example in which the theme classification break mark shown in FIG. 8 of the first embodiment is also used for the thumbnail display of the third embodiment. Hereinafter, the mark for clearly indicating the separation of the classification is referred to as a classification start mark Ts. In FIG. 9A, a classification start mark Ts1 is inserted and displayed at the beginning of each classification of 8/10, 8/11, and 8/12. In the classification start mark Ts, a date indicating the contents of the classification and a color for distinguishing the surroundings are displayed. FIG. 5B shows an example in which thumbnail images No. 22 and No. 23 selected separately are enlarged and displayed.

  Similarly to FIG. 8, the classification start mark Ts is also displayed as a representative mark indicating the classification representative (FIG. 8C). Here, the classification start mark Ts1 of 8/10 and 8/11 is selected by the user in the state of FIG. 8A, and the images belonging to this day are hidden, and the separation of 8/10 and 8/11 is made. Instead of the mark, a representative mark (Ts2) representing the classification is displayed as a classification start mark. The representative mark is displayed with a broken line added to the right side of the classification start mark.

  FIG. 4D shows an example in which a classification end mark Te that clearly indicates this is inserted and displayed at the end of an image classified by 8/9 shooting.

  As described above, in the third embodiment, since the images classified by the shooting date and time are displayed as thumbnails with separator marks and representative marks, even if the display unit 12 cannot display many images at a time with a small size. This makes it easy to search for the target image.

(Other embodiments)
Part or all of the processing of the MPU 14 described in the above embodiments may be configured by hardware. Conversely, the hardware of the image determination unit 17 may be configured by software. The specific configuration is a design matter.

  Each control process by the MPU 14 is realized by a software program stored in the ROM 16 being supplied to the MPU 14 and operating according to the supplied program. Therefore, the software program itself realizes the functions of the MPU 14, and the program itself constitutes the present invention.

  A recording medium for storing the program also constitutes the present invention. As a recording medium, besides a flash memory, an optical recording medium such as a CD-ROM or DVD, a magnetic recording medium such as an MD, a tape medium, a semiconductor memory such as an IC card, or the like can be used. Moreover, although each embodiment demonstrated the example which applied this invention to the digital camera, you may apply not only to this but the camera part of a mobile telephone, for example.

  Furthermore, the present invention is not limited to the above-described embodiment as it is, and can be embodied by modifying the constituent elements without departing from the scope of the invention in the implementation stage. In addition, various inventions can be formed by appropriately combining a plurality of components disclosed in the embodiment. For example, some components may be deleted from all the components shown in the embodiment. Furthermore, constituent elements over different embodiments may be appropriately combined.

1 is an overall block diagram of a camera 1 to which the present invention is applied in a first embodiment. FIG. 3 is a diagram illustrating an appearance of a camera held by a photographer at the time of photographing in the first embodiment. 6 is a flowchart for explaining a procedure of image theme classification and display processing in the first embodiment. 5 is a flowchart for explaining a theme determination subroutine in the first embodiment. The figure for demonstrating the principle of the face detection by the face detection part 17c in 1st Embodiment. The example which collected the image (portrait) in which only the subject was a face in 1st Embodiment. The figure which shows the screen which changes according to theme classification | category process in 1st Embodiment. The display example of a theme classification | category screen in 1st Embodiment. The flowchart explaining the process sequence for changing a display in 1st Embodiment. The figure which shows the change of a theme classification | category screen in 1st Embodiment. 9 is a flowchart for describing a procedure for classifying an image according to shooting date and time in the second embodiment. FIG. 12 is a diagram for describing the image classification processing of FIG. 11 with an image sequence in the second embodiment. 9 is a flowchart for explaining processing for performing date and time classification at the time of shooting in the second embodiment. In 3rd Embodiment, (A) is a figure which shows distribution of the imaging | photography date of the image preserve | saved at the recording medium 9a with a bar graph, (B), (C), (D) is a figure which shows each thumbnail image display. In the third embodiment, an example in which the theme category separation display shown in FIG. 8 of the first embodiment is also used for the thumbnail display of the third embodiment. 7 is a flowchart showing an example of a general user operation regarding shooting of an image and reproduction of the shot image in the problem to be solved by the invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Camera, 2 ... Shooting lens part, 2a ... AF control part, 3 ... Diaphragm part, 3a ... Diaphragm control part,
DESCRIPTION OF SYMBOLS 4 ... Imaging device, 5 ... AFE part, 6 ... Image processing part, 6a ... Sensitization part, 7 ... Compression / decompression part, 7a ... Compression part M, 7b ... Compression part S, 8 ... Recording / reproducing part, 9 ... Recording medium , 9a ... Classification file, 10 ... Input / output unit, 11 ... Display control unit, 11a ... Multi-control unit, 12 ... Display unit, 13 ... Auxiliary light emitting unit,
14 ... MPU, 14a ... theme determination unit, 14b ... date and time classification unit, 14c ... clock, 15a ... release switch, 15b ... mode switch, 15c ... other switch, 16 ... ROM,
17 ... Image determination unit, 17a ... Color determination unit, 17b ... Contrast determination unit, 17c ... Face detection unit,
20 ... Subject, 30 ... External human, 31 ... Image data,
Is1, Is2, Is3, Is4, Is5 ... Theme start mark, Ie ... Theme end mark,
Ts1, Ts2 ... Classification start mark, Te ... Classification end mark, p ... Target image, q ... Comparison image

Claims (3)

In a camera having an image classification unit that classifies images based on shooting date and time,
The image classification part
Compare the date and time of the captured image with the date and time of the previously captured image,
Determine whether the shooting date interval is within a certain period,
If it is within a certain period, determine the number of images included in the previous image classification,
If the number of included images is less than a certain number, register the captured image in the previous image classification,
A camera characterized in that if the number of included images is equal to or greater than a certain number, the photographed image is registered in a new classification different from the classification of the previous image. The said image classification | category part sets this fixed number large, so that the space | interval of imaging | photography date is shortened about the fixed number compared with the number of images included in the classification | category of the said previous image. Camera. On the computer,
Comparing the date and time of the captured image with the date and time of the previously captured image;
Determining whether the shooting date interval is within a certain period;
A step of determining the number of images included in the classification to which the previous image belongs, if within a certain period;
If the number of included images is less than a certain number, the step of registering the captured image in the previous image classification, and if the number of included images is greater than a certain number, the captured image is classified as the previous image classification. A program for executing the steps of registering in different new classifications.

Images