JP2006259788A - Image output device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To select a printing recommendation image from all of image data by grouping similar image data from a plurality of image data, and evaluating the image data. <P>SOLUTION: A printer 100 groups image data acquired from a memory card MC on the basis of photographing date and time, and similarity of images. Groups G11, G21, G22, G31, G32 and G33 are formed by grouping. The printer 100 evaluates image quality of each image data such as out-of-focus, and camera shake during photographing, and it calculates an evaluation value of each image data. Relative evaluation in a group is carried out by using the calculated evaluation values, and a relative evaluation value R of each image data is calculated. The printer 100 selects and prints image data with the top five relative evaluation values R from all of the image data as the printing recommendation image data to be recommended for printing. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to an image output apparatus that selects and outputs image data.

  In recent years, large-capacity memory cards have become widespread as recording media for digital cameras and mobile phones. A large-capacity memory card can record a large number of image data. When taking a picture with a digital camera or mobile phone using a large-capacity memory card, the user may take a plurality of images of the same subject in a short time because it can record a large number of image data. The image data of the same subject photographed in a short time is often similar. When a user desires to print an image represented by image data, the user confirms each image data recorded on the memory card and selects image data to be printed.

JP 2002-10709 A JP 2004-112596 A JP 2004-236120 A

  However, a large number of image data recorded on the memory card includes image data in which camera shake occurs and image data that is not in focus. There is a problem that it is troublesome for the user to select image data desired to be printed from a large number of image data recorded on the memory card. This problem is not a problem specific to the printing process, but is a common problem that becomes a problem even when an output device such as a display is desired to output image data.

  SUMMARY An advantage of some aspects of the invention is that it provides a technique for evaluating a large number of image data and selecting image data recommended for output.

In order to solve at least a part of the problems described above, the present invention has the following configuration. That is,
In the image output device,
Image acquisition means for acquiring a plurality of image data;
Similarity acquisition means for acquiring a similarity indicating the degree of similarity between the plurality of image data;
Classification means for classifying the plurality of image data based on the similarity;
For each image data, an evaluation value calculating means for calculating an evaluation value that is an evaluation value based on an evaluation item;
Evaluation value correction means for correcting the evaluation value of each image data classified into the same group by the classification;
Based on the corrected evaluation value that is the corrected evaluation value, output recommended image data selection means for selecting output recommended image data that recommends output;
The gist includes at least output means for outputting one or more images represented by image data including the recommended output image data.

  According to the image output apparatus of the present invention, output recommended image data can be selected from all image data based on the correction evaluation value. Accordingly, it is possible to efficiently select image data having a high evaluation from all the image data as output recommended image data while suppressing output of similar image data in duplicate.

In the image output apparatus of the present invention,
The evaluation item is image information related to image data,
The evaluation value calculation means may analyze the acquired image data to acquire image information, and calculate the evaluation value based on the acquired image information.

  According to the image output apparatus of the present invention, since the evaluation value is calculated based on the image information obtained by analyzing each image data, it is possible to perform the evaluation in consideration of the contents of the image data.

In the image output apparatus of the present invention,
The image information may be information including at least one of image quality information representing an image quality of the image data, composition information representing a composition of the image data, and photographing information representing an environment at the time of photographing the image data.

  According to the image output apparatus of the present invention, the image data can be evaluated based on various evaluation items that affect the human sense such as the image quality, composition, and shooting environment of the image data. Evaluation can be made. Therefore, it is possible to improve the evaluation accuracy of the image data.

  In the image output apparatus of the present invention, the shooting information may be stored in accompanying information attached to each image data. According to the image output apparatus of the present invention, it is possible to easily acquire shooting information by referring to the incidental information.

In the image output apparatus of the present invention,
The evaluation value correction means may calculate the corrected evaluation value by correcting the evaluation value according to the rank of the evaluation value of each image data in each classified image data group.

  According to the image output apparatus of the present invention, since the correction evaluation value can be calculated according to the rank of the evaluation values of similar image data, the correction evaluation value of the image data having a high evaluation value and the image data having a low evaluation value The difference of can be widened. Therefore, it can be suppressed that similar image data is selected as the recommended output image data.

In the image output apparatus of the present invention,
The recommended output image data selection unit may perform the selection based on the correction evaluation value and a threshold value set in common for the plurality of image data.

  Since image data with a high correction evaluation value is image data with high evaluation in the group of classified image data, according to the image output device of the present invention, similar image data is output in duplicate. In addition to the suppression, image data with high evaluation can be selected as the recommended output image data from all the image data.

In the image output apparatus of the present invention,
Furthermore,
A threshold storage unit for storing the threshold;
The output recommended image data selection unit may acquire the stored threshold value and perform the selection using the threshold value.

  According to the image output apparatus of the present invention, it is possible to select print recommended image data using a preset threshold value, and therefore it is possible to improve processing efficiency.

An image output apparatus according to the present invention,
Furthermore,
Input receiving means for receiving input from the user;
An image output apparatus comprising threshold setting means for setting the threshold based on the input.

  According to the image output apparatus of the present invention, it is possible to flexibly set a threshold value according to an input from a user.

In the image output apparatus of the present invention,
The output means further includes:
An output number acquiring means for acquiring the output number of images using the recommended output image data;
In accordance with the number of outputs, image data higher in the correction evaluation value may be selected as the recommended output image data.

  According to the image output apparatus of the present invention, it is possible to prevent similar image data from being output repeatedly and to specify the number to be output. That is, it is possible to select, as the recommended output image data, image data for the quantity specified from the top of the correction evaluation value from all the image data.

In the image output apparatus of the present invention,
The output unit may output an image represented by the recommended output image data.

  According to the image output apparatus of the present invention, since it is possible to select and output the recommended output image data from the acquired image data, it is not necessary to check all the image data and select the image data to be output. Accordingly, the burden on the user can be reduced and the convenience can be improved.

In the image output apparatus of the present invention,
Furthermore, based on the correction evaluation value, for each of the image data, comprising a recommendation degree setting means for setting a recommendation degree that represents the degree of recommendation of the output,
The output means may output information based on the recommendation degree corresponding to the image data together with an image using the image data.

  According to the image output apparatus of the present invention, it is possible to notify the user of the recommended degree of output of each image data in association with the image data. The user can select the desired image data after confirming the output image data and the recommendation level, and the convenience can be improved.

In the image output apparatus of the present invention,
The output means may output the evaluation item having a low evaluation in association with the image data for the image data having a low recommendation level.

  According to the image output device of the present invention, by outputting the contents of evaluation together with image data, it is possible to easily grasp the reason for evaluation that is difficult to understand by looking at the image data.

  The image output apparatus of the present invention may further include a display unit that displays information related to the output. According to the image output apparatus of the present invention, it is possible to display information related to output, for example, thumbnails and recommended levels of image data to be output.

In the image output apparatus of the present invention,
The classification unit may perform the classification based on at least one of information of a shooting date / time indicating the date / time when the image data was shot and a similarity indicating the degree of similarity between the image data.

  In general, since image data having similar shooting dates and times are likely to be similar, according to the image output apparatus of the present invention, image data that may be similar can be classified into the same group. In the present invention, since the corrected evaluation value is calculated and the recommended output image data is selected for the classified image data groups that are likely to be similar, the output of all image data that are likely to be similar is suppressed. be able to.

In the image output apparatus of the present invention,
The image output device is a printing device,
The output performed by the output means may be a printing process.

  According to the image output apparatus of the present invention, the printing apparatus can perform a series of processes for evaluating a plurality of acquired image data, selecting print recommended image data, and printing.

  According to the image output apparatus of the present invention, since classification is performed between adjacent image data, high-speed processing can be performed and processing efficiency can be improved.

  In the present invention, the various aspects described above can be applied by appropriately combining or omitting some of them. In addition to the configuration as the above-described image output apparatus, the present invention records an image output method by the image output apparatus, a computer program for causing the image output apparatus to output image data, and the computer program so that the computer program can be read. It can also be configured as a recording medium. In any configuration, the above-described aspects can be appropriately applied. As a computer-readable recording medium, various media such as a flexible disk, a CD-ROM, a DVD-ROM, a magneto-optical disk, an IC card, and a hard disk can be used.

Hereinafter, embodiments of the present invention will be described based on examples.
A. Example:
A1. System overview:
FIG. 1 is an explanatory diagram illustrating a system overview in the present embodiment. When the memory card MC is inserted into the card slot CS, the printer 100 acquires the image data 10 to 21 recorded on the memory card MC. The printer 100 groups the acquired image data in units of image data that are close to the shooting date. Grouping by shooting date and time is referred to as primary grouping. By the primary grouping, the image data is grouped into groups G10, G20, and G30. The printer 100 further groups the image data based on the similarity between the image data in each primary group. Grouping based on similarity between image data is called secondary grouping. By the secondary grouping, a group G11 is formed from the group G10, two groups G21 to G22 are formed from the group G20, and groups G31, G32, and G33 are formed in the group G30. That is, the image data 10 to 21 are grouped into six groups of group G11, group G21, group G22, group G31, group G32, and group G33.

  The printer 100 evaluates the image quality of each image data, for example, whether or not a focus shift has occurred during shooting, and whether or not camera shake has occurred, and calculates an evaluation value for each image data. Using the calculated evaluation value, a relative evaluation within the group is performed, and a relative evaluation value R of each image data is calculated. For example, as illustrated, the relative evaluation value R of the image data 10 is 70, and the relative evaluation value R of the image data 11 is 60.

  The printer 100 selects and prints image data up to the top five relative evaluation values R as image data for which printing is recommended (hereinafter referred to as recommended printing image data) from all the image data. That is, in the present embodiment, hatched image data 10, 11, 13, 16, 17 are selected as recommended print image data. As described above, in this embodiment, the printer 100 groups a plurality of pieces of image data according to the shooting date / time and the similarity of the image data. For each grouped image data, the printer 100 calculates an evaluation value based on a predetermined evaluation item, and selects print recommended image data using the evaluation value, thereby improving convenience. .

A2. Function block:
FIG. 2 is an explanatory diagram illustrating functional blocks of the printer 100 in this embodiment. The printer 100 includes a CPU 101, an interface 102, a display panel 103, an operation unit 104, a print execution unit 105, a spooler 106, a RAM 110, and a ROM 120. Each functional block is controlled by the CPU 101. The RAM 110 is a readable / writable memory. In the RAM 110, an image data storage area 111 and a grouping information storage area 112 are formed. The ROM 120 includes an image data acquisition module 121, a grouping module 122, an absolute evaluation value calculation module 123, an evaluation value correction module 124, a recommended print image selection module 125, and a display control module 126. Each module included in the ROM 120 is configured by software. Each module may be configured in hardware.

  The interface 102 is an interface for connecting the memory card MC. The interface 102 is configured as a part of the card slot CS. The operation unit 104 is an interface that receives input from the user.

  The image data acquisition module 121 reads image data from the memory card MC via the interface 102 and records it in the image data storage area 111.

  The grouping module 122 primarily groups the image data stored in the image data storage area 111 according to the shooting date and time. The grouping module 122 further performs secondary grouping for each group that has been subjected to primary grouping based on the similarity of image data. The grouping module 122 generates grouping information indicating to which group the image data belongs and stores it in the grouping information storage area 112.

  In the evaluation value information storage area 130, an analysis result of image data and an evaluation value corresponding to the analysis result are stored for each evaluation item. In the load value information storage area 131, load value information for each evaluation item for weighting the evaluation value for each item calculated for each item is stored.

  Based on the analysis result of the image data, the evaluation value stored in the evaluation value information storage area 130, and the load value stored in the load value information storage area 131, the absolute evaluation value calculation module 123 An absolute evaluation value is calculated. The absolute evaluation value corresponds to “evaluation value” in the present invention, and the absolute evaluation value calculation module 123 corresponds to “evaluation value calculation means” in the present invention.

  The evaluation value correction module 124 corrects the absolute evaluation value of each image data so as to widen the difference between the absolute evaluation values based on the rank of the absolute evaluation values in each group that is secondarily grouped. The absolute evaluation value after correction is called a correction evaluation value.

  The recommended print image selection module 125 selects image data having correction evaluation values up to the top five out of all the image data as recommended print image data, and passes it to the spooler 106.

  The print execution unit 105 reads out the image data from the spooler 106 and prints it.

A3. Printing process:
FIG. 3 is a flowchart for explaining print processing in the present embodiment. The printer 100 acquires the image data recorded on the memory card MC and stores it in the image data storage area 111 (step S10). The printer 100 groups the image data stored in the image data storage area 111 (step S11). Specifically, the shooting date and time included in the supplementary information of the image data is acquired, and primary grouping is performed using the acquired shooting date and time as a key (step S12), and the image data of each primary group is grouped. Based on the similarity, secondary grouping is performed (step S13).

  Details of the primary grouping process will be described with reference to FIG. 4, and details of the secondary grouping process will be described with reference to FIG. Further, the grouping process will be schematically described as appropriate with reference to FIG.

  FIG. 4 is a flowchart for explaining the grouping process by shooting date and time, that is, the primary grouping process in the present embodiment. The printer 100 rearranges the image data stored in the image data storage area 111 in ascending order of shooting date and time (step S20), the image data to be classified, and the rearranged order immediately before the classification target image data. The photographing date / time of the image data is acquired (step S21). The printer 100 calculates the shooting interval of both image data from the acquired shooting date and time (step S22).

  The printer 100 determines whether the shooting interval is less than one hour (step S23). If the shooting interval is less than one hour (step S23: YES), the printer 100 classifies the image data with the latest shooting date and time into the same group as the image data with the earlier shooting date and time (step S24).

  When the shooting interval is 1 hour or longer (step S23: NO), a new group is generated, and the classification target image data is classified into a group different from the previous image data (step S25).

  The printer 100 determines whether the grouping of all the image data has been completed (step S26). When the grouping of all the image data is finished (step S26: YES), this process is finished. If the grouping of all the image data has not been completed (step S26: NO), the grouping process is continued from step S21.

  The processing so far is schematically shown using FIG. Image data 10 to 16 illustrated in FIG. 6 is an example of image data stored in the image data storage area 111. The image data 10 to 16 are image data photographed on the same day, and a balloon attached to each image data represents the photographing time of each image data.

  As shown in the figure, the image data are rearranged in ascending order of shooting date and time. The shooting time of the image data 10 that is the first image data is “9:05:23”, and the shooting time of the image data 11 that is the second image data is “12:10:10”. The shooting interval of both image data is “3 hours 4 minutes 47 seconds”, and the image data 10 and the image data 11 are classified into different groups with the grouping line P1 as a boundary. The grouping lines P1 and P2 represent boundaries where the shooting interval is 1 hour or more. From the shooting time of the image data 11 and the shooting time of the image data 12, the shooting interval of both image data is calculated. Since the shooting interval is “5 minutes”, the image data 11 and the image data 12 are classified into the same group. Further, since the shooting interval between the image data 15 and the image data 16 is “3 hours 12 minutes 7 seconds”, the image data 15 and the image data 16 are classified into different groups with the grouping line P2 as a boundary. As described above, the image data is classified into groups G10, G20, G30,.

  FIG. 5 is a flowchart for explaining the grouping process based on the similarity of image data in this embodiment. This is a process executed by the grouping module 122 on the primary grouped image data based on the shooting date and time described with reference to FIG.

  The grouping module 122 calculates the similarity between the classification target image data and the immediately preceding image data in the primary grouped group (step S30). Specifically, the grouping module 122 creates a histogram of the luminance values of both image data, and calculates the similarity S between the two image data using Equation 1. Ni and Mi represent the relative frequencies of class i of the luminance histogram, and ΣNi = 1 and ΣMi = 1.

  The grouping module 122 determines whether or not the similarity S is higher than the threshold ThSimi (step S31), and when the similarity S is higher than the threshold ThSimi (step S31: YES). The classification target image data is determined to be similar to the previous image data, and is classified into the same group as the previous image data (step S32). When the similarity S is equal to or less than the threshold ThSimi (step S31: NO), the grouping module 122 determines that the two image data are dissimilar, and the classification target image data is different from the previous image data. Sort into groups (step S32).

  The grouping module 122 determines whether or not the secondary grouping of the image data has been completed for each group that has been primary grouped according to the shooting date and time (step S34). If the secondary grouping of the image data in the group has not been completed (step S34: NO), the process returns to step S30 and the secondary grouping process is continued. When the secondary grouping of the image data in the group is completed (step S34: YES), it is determined whether or not the secondary grouping has been performed on all the groups that have been grouped into the primary group (step S35). ). If the secondary grouping for all the primary groups has not been completed (step S35: NO), the next group is referred to (step S36), the process returns to step S30, and the secondary grouping process is performed. continue.

  The processing up to this point will be described using the group G20 as an example with reference to FIG. As shown in the drawing, the similarity S1 between the adjacent image data 12 and the image data 13 is equal to or lower than ThSimi, so that the image data 12 and the image data 13 are classified into different groups. A grouping line Q represents a group boundary. Since the similarity S2 between the adjacent image data 13 and the image data 14 is higher than ThSimi, the image data 13 and the image data 14 are classified into the same group G22.

  The grouping module 122 generates and stores grouping information related to grouping (step S37) when the secondary grouping has been completed for all the groups that have been primary grouped (step S35: YES).

  The contents of the generated grouping information 160 will be described with reference to FIG. FIG. 7 is an explanatory diagram illustrating the grouping information 160 in the present embodiment. The grouping information 160 is stored in the grouping information storage area 112. The evaluation value table 200 includes image data specifying information and a group name of the secondary group. Image data specifying information is information for specifying image data separately. For example, the image data 15 represents being grouped into a group G22.

  After completing the grouping process, the printer 100 performs a process of calculating an absolute evaluation value (step S14).

  The absolute evaluation value calculation process will be described in detail with reference to FIG. FIG. 8 is a flowchart for explaining the absolute evaluation value calculation processing in the present embodiment. This process is a process executed by the absolute evaluation value calculation module 123.

  The absolute evaluation value calculation module 123 analyzes the first image data of the image data rearranged in ascending order of the shooting date and time, that is, the image data with the earliest shooting date and time (step S41), and classifies each item based on the evaluation item. An evaluation value is calculated (step S42). In the present embodiment, the absolute evaluation value calculation module 123 performs evaluation based on three evaluation items: focus evaluation at the time of shooting, evaluation of camera shake occurring at the time of shooting, and clipping evaluation representing overexposure at the time of shooting.

  Evaluation values for focus deviation evaluation and camera shake evaluation will be described with reference to FIG. 9, and evaluation values for clipping evaluation will be described with reference to FIG. FIG. 9 is an explanatory diagram illustrating an evaluation value table 200 in the present embodiment. The evaluation value table 200 includes a focus deviation amount (unit: mm) and item-specific evaluation values. The out-of-focus amount represents the out-of-focus amount obtained by analyzing the image data, and the evaluation value for each item represents the evaluation value for each item corresponding to the out-of-focus amount. The absolute evaluation value calculation module 123 calculates an out-of-focus amount by applying an edge extraction filter to the image data and calculating an average of the widths of the extracted edges. For example, when the focus shift amount is 6.4 mm, the evaluation value for each item is “9”.

  Also in the camera shake evaluation, the evaluation value table 200 is applied to obtain the evaluation value for each item. That is, by setting the amount of focus shift to the amount of blur obtained by analyzing the image data, it is possible to acquire the evaluation value for each item according to the amount of blur. For example, when the blur amount is 6.4 mm, the evaluation value for each item is “9” as in the case of the focus shift amount. The absolute evaluation value calculation module 123 applies an edge extraction filter to the image data, calculates the average of the edge widths for each edge direction, and sets the maximum width as the blur amount.

  FIG. 10 is an explanatory diagram illustrating an evaluation value table 210 for clipping evaluation in the present embodiment. The evaluation value table 210 includes a ratio (%) at which the luminance value is 255 or 0 and item-specific evaluation values. “The ratio of the luminance value of 255 or 0” represents the ratio of pixels having the luminance value of 255 or 0 of the image data with respect to all the pixels of the image data. The evaluation value according to item according to the ratio is shown. For example, for a certain image data, when the ratio of pixels having a luminance value of 255 or 0 is 11% with respect to the total number of pixels, the item-specific evaluation value is “6”. In this embodiment, the width of the evaluation value for each item in the evaluation value table 210 is “2”. However, the ratio of pixels having a luminance value of 255 or 0 is set in more detail, and the width of the evaluation value for each item. May be set to “1”.

  The absolute evaluation value calculation module 123 applies a load set for each evaluation item to the evaluation value for each item, and calculates a temporary evaluation value for each evaluation item (step S43).

  The load for each evaluation item will be described with reference to FIG. FIG. 11 is an explanatory diagram illustrating a load table 300 representing loads for each item evaluation in the present embodiment. The load table 300 includes evaluation items and load values. The load table 300 includes evaluation items and load values. For example, the load applied to the evaluation value for each item of defocus is 40. Similarly, the load applied to the evaluation value for each item of camera shake evaluation is 40, and the load applied to the evaluation value for each item of clipping evaluation is 20. Each load value is not limited to the values exemplified in the load table 300, and may be arbitrarily set. It is preferable to set a high load value for each evaluation item that is considered to have a strong influence on human vision with respect to the image quality of the image represented by the image data.

  The absolute evaluation value calculation module 123 determines whether or not provisional evaluation values have been calculated for all evaluation items (step S44). If calculation of temporary evaluation values has not been completed for all evaluation items (step S44: NO), the absolute evaluation value calculation module 123 performs processing from step S41 and calculates temporary evaluation values for each evaluation item. When the calculation of the temporary evaluation values is completed for all the evaluation items (step S44: YES), the absolute evaluation value calculation module 123 calculates an absolute evaluation value that is an integrated value of all the calculated temporary evaluation values ( Step S45).

  After completing the absolute evaluation value calculation process, the printer 100 performs an evaluation value correction process (step S15).

  The evaluation value correction process will be described in detail with reference to FIG. FIG. 12 is a flowchart for explaining evaluation value correction processing in the present embodiment. This process is a process executed by the evaluation value correction module 124.

  The evaluation value correction module 124 refers to the absolute evaluation values of the image data included in the first secondary group (step S50), and ranks from the first to the Nth in descending order of the absolute evaluation values of the image data in the group. Is added (step S51). N is a natural number, and the maximum value is the number of image data included in each group that is secondarily grouped.

  The evaluation value correction module 124 calculates the correction evaluation value of the image data by applying Equation 2 shown below (step S52). Note that N is a rank in each group of image data, and H is a predetermined correction coefficient.

  According to Expression 2, the absolute evaluation value of the image data having the second or lower absolute evaluation value in each group is lowered by a correction amount proportional to the rank.

  The relationship between the absolute evaluation value and the corrected evaluation value will be described with reference to FIG. FIG. 13 is an evaluation value graph 400 in the present embodiment. The evaluation value graph 400 is a graph in which the absolute evaluation value and the corrected evaluation value are plotted in order of photographing date / time. The horizontal axis represents image data arranged in order of shooting date and time, and the vertical axis represents an evaluation value.

  The image data 13, 14, and 15 included in the secondary group G22 will be described as an example. The evaluation value 130a represents the absolute evaluation value of the image data 13, the evaluation value 140a represents the absolute evaluation value of the image data 14, and the evaluation value 150a represents the absolute evaluation value of the image data 15 (hereinafter referred to as the evaluation value 130a). Absolute evaluation value 130a, evaluation value 140a is called absolute evaluation value 140a, and evaluation value 150a is called absolute evaluation value 150a). In the descending order of the absolute evaluation values 130a, 140a, and 150a, the image data 13 is ranked first, the image data 14 is ranked second, and the image data 15 is ranked third. The absolute evaluation values of the second and subsequent image data are corrected by applying Equation 2 described above.

  For example, the absolute evaluation value 140a of the image data 14 is second in the group G22. Therefore, the correction evaluation value 140b is a value obtained by subtracting the correction coefficient H from the absolute evaluation value 140a as shown in the figure. Similarly, since the absolute evaluation value 150a of the image data 15 is third in the group G22, the corrected evaluation value 150b is a value that is lowered by 2H from the absolute evaluation value 150a as shown in the figure.

  The printer 100 selects the top five calculated correction evaluation values R as image data recommended for printing (step S16).

  The recommended print image data selection process will be described in detail with reference to FIG. FIG. 14 is a flowchart for explaining print recommendation image data selection processing in the present embodiment. This process is a process executed by the recommended print image selection module 125.

  The recommended print image selection module 125 refers to the correction evaluation values of all the image data (step S60), and selects image data up to the top five of the correction evaluation values (step S61). The recommended print image selection module 125 stores the selected image data in the spooler 106 in ascending order of the shooting date and time of each image data (step S62).

  The printer 100 sequentially prints the image data stored in the spooler 106 (step S17).

  According to the printer 100 of the first embodiment described above, similar image data is classified into the same group, and the absolute difference between the absolute evaluation values of the image data is widened based on the rank of the absolute evaluation values in the group. Since the evaluation value is corrected, and the recommended print image data is selected from all the image data based on the corrected evaluation value, it is possible to suppress similar image data from being duplicated and to evaluate the evaluation item from all the image data. It is possible to efficiently select image data having a high evaluation based on. Also, it is possible to select image data having a high evaluation by designating a desired number of prints from all image data.

  In addition, according to the present embodiment, when a human visually recognizes image data, a high load is set for an evaluation item that is considered to have a strong influence on the determination of whether the image quality is good or bad. By doing so, it is possible to calculate an absolute evaluation value that matches a human sense.

  Further, according to the present embodiment, the image data can be evaluated by using a plurality of evaluation items, so that the image data can be evaluated from various aspects.

B. Second embodiment:
In the first embodiment described above, the printer 100 selects image data from all the image data recorded on the memory card MC to the top five correction evaluation values as recommended print image data. In the second embodiment, the printer 100 sets a recommended printing level indicating the recommended printing level for each image data based on the correction evaluation value, and associates the recommended printing level with the image data on the display panel 103. I decided to display it. In this embodiment, all the processes except for the configuration of the printer 100 and the recommended print image data selection process are the same as those in the first embodiment.

B1. Recommended printing image data selection process:
FIG. 15 is a flowchart for explaining print recommendation image data selection processing in the second embodiment. The printer 100 refers to the calculated correction evaluation value and recommendation level setting information of all image data (step S70), sets the recommended printing level for each image data, and creates recommendation level information (step S71).

  The recommendation level setting information will be described with reference to FIG. 16, and the recommendation level information will be described with reference to FIG. FIG. 16 is an explanatory diagram illustrating recommendation level setting information 500 in the present embodiment. The recommendation level setting information 500 includes a correction evaluation value and a print recommendation level. For example, the recommended printing level of image data with a correction evaluation value of 74 is “3”, and the recommended printing level of image data with a correction evaluation value of 58 is “1”. The recommendation level setting information 500 is stored in the ROM 120 in advance.

  FIG. 17 is an explanatory diagram illustrating recommendation level information 510 in the present embodiment. The recommendation level information 510 includes image data specifying information and a print recommendation level. The image data specifying information is information for specifying image data. The print recommendation level is a print recommendation level set for each image data. For example, the recommended printing degree of the image data 11 is “2”. The printer 100 generates recommendation degree information 510 and stores it in the RAM 110.

  The printer 100 refers to the recommendation level information 510 and displays the image data and information indicating the recommended print level corresponding to the image data on the display panel 103 (step S72).

  The display contents of the display panel 103 will be described with reference to FIG. FIG. 18 is a display example of the display panel 103 in this embodiment. On the display panel 103, print guide information 150, thumbnails 10a to 15a of image data 10 to 15 stored in the image data storage area 111, a recommendation level icon 610, and evaluation information 620 are displayed.

  The recommendation level icon 610 represents the recommended printing level of each image data. The recommendation level icon 610 is a star-shaped figure corresponding to the number of recommendation level values. The recommendation level icon 610 is displayed on the thumbnail. The evaluation information 620 represents an evaluation item having a low item-specific evaluation value of the image data.

  The print guide information 150 includes pattern information 600, 601, 602, and 603 representing print patterns in consideration of the print recommendation level, and radio buttons 600a, 601a, 602a, and 603a associated with the pattern information.

  For example, a recommendation icon including three star-shaped figures is displayed on the thumbnail 10a and the thumbnail 13a. That is, the image data 10 and the image data 13 representing the thumbnail 10a and the thumbnail 13a are image data having a recommendation level “3”. The user designates a print pattern by selecting one of the radio buttons.

  When the printer 100 receives designation of a print pattern from the user (step S73), the printer 100 selects print recommended image data according to the designated print pattern (step S74) and stores it in the spooler 106 (step S75).

  As shown in FIG. 18, for example, when the radio button 602a is selected by the user, the printer 100 displays the thumbnail 10a, the thumbnail 11a, and the image data 10, the image data 11, and the image data 13 representing the thumbnail 13a as print recommended images. Select as data.

  According to the printer 100 of the second embodiment described above, it is possible to display the print recommendation level and the thumbnail on the display panel. The contents of the image represented by the data can be confirmed. In addition, since the print pattern is set according to the print recommendation level, it is possible to reduce the burden of selecting image data one by one and easily select image data to be printed.

  According to the present embodiment, since the evaluation information 620 is displayed in correspondence with the thumbnail, it is possible to easily know evaluation items with low evaluation. Accordingly, it is possible to reduce the load of checking image data by browsing, enlarging, or the like.

C. Variations:
(1)
In the first embodiment described above, focus evaluation, camera shake evaluation, and clipping evaluation are performed to calculate an absolute evaluation value, but the present invention is not limited to this. For example, the composition of the image represented by the image data may be one of the evaluation items.

  Calculation of the evaluation value for each item by composition evaluation of the image will be described with reference to FIGS. FIG. 19 is an explanatory diagram schematically illustrating the composition of image data in the present modification. The area indicated by hatching in the figure represents a human face area. The center O represents the center of the image data 30, and the center of gravity P represents the center of gravity of the human face area. The distance D represents the number of pixels corresponding to the linear distance between the center O and the center of gravity P. The unit of the distance D is a pixel.

  The printer 100 analyzes the image data to extract a human face area, and calculates a distance D from the central portion of the image data to the extracted face area. An item-specific evaluation value may be calculated based on the distance D and an evaluation value table described below.

  FIG. 20 is an explanatory diagram illustrating an evaluation value table 700 in this modification. The evaluation value table 700 includes a distance D from the image center and item-specific evaluation values. The distance D from the center of the image is the distance D described in FIG. The item-specific evaluation value represents an evaluation value corresponding to the distance D. For example, when the distance D is 68 pixels, the evaluation value for each item in the composition evaluation of the image data is “8”.

  According to this modification, not only the evaluation based on the image quality such as camera shake and the focus shift but also the composition of the image data can be evaluated. Accordingly, the calculated evaluation value can be further matched with the human sense, and the selection accuracy of the recommended print image data can be improved.

  Moreover, it is good also as an evaluation item including whether a specific person is included in the image represented by image data by analyzing image data and performing person recognition. Alternatively, face extraction may be performed by analyzing image data, and the ratio of the face area to the entire image data may be included in the evaluation item.

(2)
In the first embodiment described above, the image data is analyzed and the camera shake evaluation is performed based on the blur amount of the subject. However, the present invention is not limited to this. For example, camera shake evaluation may be performed on the basis of image information attached to image data, for example, camera shake information included in Exif information.

  FIG. 21 is an explanatory diagram illustrating the incidental information 50 in the present modification. The incidental information 50 represents image information incidental to the image data. As shown in the figure, the accompanying information 50 includes various image capturing conditions when the image file 20 is captured, such as “color space information”, “ISO”, as well as information related to the image file 20 such as “image title” and “shooting date / time”. “Sensitivity”, “Shutter speed”, and “Focal distance” are recorded. “Camera shake information” represents the amount of camera shake caused by camera shake at the time of shooting as an angular velocity measured by a gyro sensor provided in the digital camera. The angular velocity is an angle at which the digital camera moves in one second.

  The printer 100 acquires camera shake information included in the incidental information 50, and calculates an evaluation value for each item of camera shake evaluation based on the camera shake information and an evaluation value table described below.

  FIG. 22 is an explanatory diagram illustrating an evaluation value table 800 in this modification. The evaluation value table 800 includes camera shake information and item-specific evaluation values. The camera shake information represents camera shake information included in the Exif information, and the item-based evaluation value represents an evaluation value corresponding to the value of the camera shake information. When a range is set in the camera shake information of the evaluation value table 800, the camera shake information is a value larger than the start value of the range and included below the end value of the range. For example, in the case of “0 to 3”, the camera shake information includes a value that is greater than the range start value “0” and less than or equal to the range end value “3”.

  In this modification, the camera shake information included in the Exif information 50 is “10 ° / sec”, and thus the item-specific evaluation value is “4”.

  According to this modification, it is possible to reduce the processing load for analyzing image data by performing item evaluation using the accompanying information attached to the image. Further, the processing speed can be improved by using Exif information that can be easily referred to.

(3)
In the first embodiment described above, the image data with the highest relative evaluation value from all the image data is selected as the recommended print image data. However, the present invention is not limited to this. For example, image data having a relative evaluation value equal to or greater than a threshold value ThVal common to all image data may be selected as recommended print image data.

  The recommended print image data selection process in this modification will be described in detail with reference to FIG. FIG. 23 is a flowchart for explaining print recommendation image data selection processing according to the modification. The printer 100 acquires the correction evaluation value of the image data (step S80), and determines whether or not the correction evaluation value is higher than the threshold value ThVal (step S81). If the correction evaluation value is higher than the threshold ThVal (step S81: YES), the printer 100 selects image data having the correction evaluation value as print recommended image data (step S82) and stores it in the spooler 106 (step S82). Step S83).

  The printer 100 determines whether the image data that has been determined to be print recommended image data is the last image data of the image data stored in the image data storage area 111 (step S84). If it is the last image data (step S84: YES), the process ends. If it is not the last image data (step S84: NO), the correction evaluation value of the next image data is acquired (step S80), and the process is repeated.

  If the correction evaluation value is equal to or less than the threshold ThVal (step S81: NO), the printer 100 continues the process from step S84.

  For example, when the threshold ThVal = 50, as shown in FIG. 13, the image data having a correction evaluation value higher than the correction evaluation value ThVal (= 50) is image data 10, 11, 13, 14, 16, 17, 19 and 20. Therefore, the printer 100 selects these image data as recommended print image data.

  According to this modification, the recommended print image data can be selected using a threshold common to all the image data, so that the burden of selecting image data to be printed from similar image data is reduced and the overall image quality is good. Image data can be selected and output.

(4)
In the first embodiment described above, the similarity between the image data is calculated using the luminance histogram, but the present invention is not limited to this. For example, the difference between the pixel values of the corresponding pixels between the image data may be used, or the degree of similarity is calculated using a feature amount obtained by analyzing the image data, for example, a distribution or ratio of RGB values. It is good.

(5)
In the first embodiment described above, two-hour grouping is performed based on the similarity calculated for adjacent image data, but the present invention is not limited to this. For example, the similarity may be calculated by using three pieces of image data including the preceding and following image data, and grouping may be performed, or the similarity between a plurality of image data may be calculated and grouped. Also good. In this way, grouping based on similarity can be performed in detail.

(6)
In the second embodiment described above, the print recommendation level is displayed on the display panel together with the image data, but the present invention is not limited to this. For example, the same content as that displayed on the display panel may be printed, or may be printed without being displayed on the display panel.

(7)
In the first embodiment described above, the printer 100 selects the recommended print image data, but the present invention is not limited to this. For example, a module is connected to a printer and a personal computer via a local area network, and the personal computer selects print recommended image data (the grouping module 122 and the absolute evaluation value calculation module in the first embodiment of the present invention). 123, an evaluation value correction module 124, and a recommended print image selection module 125).

(8)
In the first embodiment described above, correction for lowering the evaluation by (N−1) × H is performed for the absolute evaluation values of the second and lower ranks, but is not limited thereto. For example, correction for raising the absolute evaluation value of image data having a high absolute evaluation value may be performed.

(9)
In the second embodiment described above, the print recommendation level is set according to the value of the correction evaluation value, but the present invention is not limited to this. For example, the recommended printing degree of image data having correction evaluation values in the top five places is set to “3”, and the recommended printing degree of image data having correction evaluation values from the sixth place to the tenth place is set to “2”, etc. As described above, the recommended printing degree may be set based on the order.

(10)
In the second embodiment described above, the print pattern based on the recommended print degree is set, but the present invention is not limited to this. For example, the user may check the recommended printing degree and thumbnail displayed on the display panel, and arbitrarily select image data to be printed. In this way, it is possible to flexibly select image data to be printed.

  Although various embodiments of the present invention have been described above, it is needless to say that the present invention is not limited to these embodiments and can take various configurations without departing from the spirit of the present invention.

Explanatory drawing which illustrates the system outline | summary in 1st Example. FIG. 3 is an explanatory diagram illustrating a functional block of a printer in the first embodiment. 6 is a flowchart for explaining print processing according to the first embodiment. 6 is a flowchart for explaining grouping processing by shooting date and time in the first embodiment. 5 is a flowchart for explaining grouping processing based on similarity of image data in the first embodiment. The schematic diagram explaining the grouping process in 1st Example. Explanatory drawing which illustrates the grouping information in 1st Example. The flowchart explaining the absolute evaluation value calculation process in 1st Example. Explanatory drawing which illustrates the evaluation value table | surface of focus deviation evaluation in 1st Example. Explanatory drawing which illustrates the evaluation value table | surface of clipping evaluation in 1st Example. Explanatory drawing which illustrates the load table in 1st Example. The flowchart explaining the evaluation value correction process in 1st Example. It is an evaluation value graph in the 1st example. 4 is a flowchart for explaining recommended print image data selection processing in the first embodiment. 12 is a flowchart for explaining recommended print image data selection processing according to the second embodiment. Explanatory drawing which illustrates the recommendation level setting information in 2nd Example. Explanatory drawing which illustrates the recommendation level information in 2nd Example. The display example of the display panel in 2nd Example. Explanatory drawing explaining the composition of the image data in a modification. Explanatory drawing which illustrates the evaluation value table | surface of composition evaluation in a modification. Explanatory drawing which illustrates incidental information in a modification. Explanatory drawing which illustrates the evaluation value table of camera shake evaluation in a modification. 9 is a flowchart for explaining recommended print image data selection processing according to a modification.

Explanation of symbols

10 to 21 Image data 10a to 15a Thumbnail 100 Printer 101 CPU
DESCRIPTION OF SYMBOLS 102 ... Interface 103 ... Display panel 104 ... Operation part 105 ... Print execution part 106 ... Spooler 110 ... RAM
DESCRIPTION OF SYMBOLS 111 ... Image data storage area 112 ... Grouping information storage area 121 ... Image data acquisition part 122 ... Grouping module 123 ... Absolute evaluation value calculation module 124 ... Evaluation value correction module 125 ... Print recommendation image selection module 126 ... Display control module 130a , 140a, 150a ... absolute evaluation value 150 ... printing guide information 160 ... grouping information 200 ... evaluation value table 210 ... evaluation value table 300 ... load table 400 ... evaluation value graph 500 ... recommendation degree setting information 510 ... recommendation degree information 610 ... Recommendation level icon 620 ... Evaluation information 600, 601, 602, 603 ... Pattern information 600a, 601a, 602a, 603a ... Radio button 700 ... Evaluation value table 800 ... Evaluation value table

Claims (16)

An image output device,
Image acquisition means for acquiring a plurality of image data;
Similarity acquisition means for acquiring a similarity indicating the degree of similarity between the plurality of image data;
Classification means for classifying the plurality of image data based on the similarity;
For each image data, an evaluation value calculating means for calculating an evaluation value that is an evaluation value based on an evaluation item;
Evaluation value correction means for correcting the evaluation value of each image data classified into the same group by the classification;
Based on the corrected evaluation value that is the corrected evaluation value, output recommended image data selection means for selecting output recommended image data that recommends output;
An image output apparatus comprising: at least output means for outputting one or more images represented by image data including the recommended output image data. The image output apparatus according to claim 1,
The evaluation item is image information related to image data,
The evaluation value calculation means is an image output device that analyzes the acquired image data to acquire image information, and calculates the evaluation value based on the acquired image information. The image output device according to claim 2,
The image information is information including at least one of image quality information representing the image quality of the image data, composition information representing the composition of the image data, and photographing information representing an environment at the time of photographing the image data. Output device. The image output device according to claim 3,
The imaging information is an image output device stored in incidental information attached to each image data. The image output device according to any one of claims 1 to 4,
The evaluation value correction means calculates the corrected evaluation value by correcting the evaluation value according to the rank of the evaluation value of each image data in each classified image data group. The image output device according to any one of claims 1 to 5,
The output recommended image data selection unit is an image output device that performs the selection based on the correction evaluation value and a threshold value set in common for the plurality of image data. The image output device according to claim 6,
Furthermore,
A threshold storage unit for storing the threshold;
The output recommended image data selection means is an image output device that performs the selection using the stored threshold value. The image output device according to claim 6,
Furthermore,
Input receiving means for receiving input from the user;
An image output apparatus comprising threshold setting means for setting the threshold based on the input. The image output device according to any one of claims 1 to 5,
The output means further includes:
An output number acquiring means for acquiring the output number of images using the recommended output image data;
An image output apparatus that selects, as the recommended output image data, image data that is higher in the correction evaluation value in accordance with the number of outputs. The image output device according to any one of claims 1 to 9,
The output means outputs an image represented by the recommended output image data. The image output device according to any one of claims 1 to 9,
Furthermore, based on the correction evaluation value, for each of the image data, comprising a recommendation degree setting means for setting a recommendation degree that represents the degree of recommendation of the output,
The output means outputs an information based on the recommendation level corresponding to the image data together with an image using the image data. The image output device according to claim 11,
The output means outputs an evaluation item with a low reputation in association with an image using the image data for the image data with a low recommendation level. The image output device according to claim 11 or 12,
Furthermore,
An image output apparatus comprising a display unit for displaying the information to be output. The image output device according to any one of claims 1 to 13,
The classification means performs image classification based on at least one of information on a shooting date and time indicating the date and time when the image data was shot and a similarity indicating a degree of similarity between the image data. apparatus. 15. The image output device according to claim 1, wherein
The image output device is a printing device,
The output performed by the output means is an image output device that is a printing process. An image output method performed by an image output device,
Obtaining a plurality of image data, obtaining a similarity indicating a degree of similarity between the plurality of image data,
Classifying the plurality of image data based on the similarity of the plurality of image data;
For each image data, calculate an evaluation value that is an evaluation value based on the evaluation item,
Correcting the evaluation value of each image data classified into the same group by the classification,
Based on the corrected evaluation value that is the corrected evaluation value, select output recommended image data that recommends output,
An image output method for outputting at least one image represented by image data including at least the output recommended image data.

Images