JP2004236170A - Image data processing method, image data processing apparatus and program, and storage medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image data processing method for relieving a job load in the case of extracting image data to be outputted among a plurality of image data by sorting a plurality of the image data in orders of 'well taken' image data. <P>SOLUTION: The image data processing method for revising an output sequence of a plurality of outputted image data includes: a correction step of correcting the image data; a correction amount calculation step (step S803) for calculating a correction amount on the basis of the image data before being corrected in the correction step and the image data after the correction; and a revision step (step S806) for revising the output sequence to output a plurality of the image data in the order of smaller calculated correction amount. <P>COPYRIGHT: (C)2004,JPO&NCIPI

Description

[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to a technique for processing image data.
[0002]
[Prior art]
A system in which image data is photographed using a digital camera and the data is transferred to a printer via a PC or directly to execute printing is already being generalized. As a result, the capacity of the memory card has increased, and as a result, a large amount of image data can be captured by a digital camera at one time.
[0003]
However, printing all of the image data requires a great deal of cost. Therefore, the user has attempted to reduce the printing cost by extracting image data to be printed from image data shot in large quantities and printing only the extracted image data.
[0004]
However, the task of extracting several pieces of image data from hundreds of images requires a great deal of labor. Therefore, it is desired to realize a function of automatically sorting a large amount of image data in the order of image data to be printed.
[0005]
As a technique for automatically sorting image data, for example, JP-A-2000-207405 is cited. According to the publication, it is possible to automatically sort image data according to the feature amount of an image such as luminance.
[0006]
[Patent Document 1]
JP 2000-207405 A
[Problems to be solved by the invention]
However, the image data sorting method shown in the above-described conventional example sorts the image data according to a predetermined feature amount of the image data, and is not necessarily sorted in an order desired by the user.
[0008]
The image data to be printed for the user is generally image data that is “good”, and therefore, when printing or displaying image data, “good” is performed in advance. Sorting is required in the order of image data.
[0009]
The present invention has been made in view of the above-described problem, and sorts a plurality of image data in the order of the image data that is “taken well” so that the image data to be output from the plurality of image data is sorted out. The purpose is to reduce the work load at the time of extraction.
[0010]
[Means for Solving the Problems]
In order to achieve the above object, an image data processing method according to the present invention has the following configuration. That is,
An image data processing method for changing an output order of a plurality of output image data,
A correction step of correcting the image data,
A correction amount calculating step of calculating a correction amount based on the image data before being corrected by the correcting step and the corrected image data;
Changing the output order for outputting the plurality of image data in ascending order of the calculated correction amount.
[0011]
BEST MODE FOR CARRYING OUT THE INVENTION
[First Embodiment]
In the present embodiment, a method will be described in which a correction amount is calculated for a specified image data group, and a sort process is executed based on the correction amount.
[0012]
(1) System Configuration FIG. 1 is a block diagram showing a system configuration of an image data processing apparatus according to an embodiment of the present invention. The input device 101 is a device for inputting instructions and data from a user, and includes a pointing system such as a keyboard and a mouse. The display device 102 is a device that displays a GUI or the like, and usually uses a CRT, a liquid crystal display, or the like.
[0013]
The storage device 103 is a device that stores image data, programs, and the like, and usually uses a hard disk. Reference numeral 104 denotes a CPU, which is involved in all of the above-described processing of each configuration. The ROM 105 and the RAM 106 provide programs, data, a work area, and the like necessary for the processing to the CPU 104. Further, it is assumed that a control program necessary for the processing of the subsequent flowcharts is stored in the storage device 103 or in the ROM 105. If the data is stored in the storage device 103, the data is temporarily read into the RAM 106 and then executed.
[0014]
The system configuration of the image data processing apparatus according to the embodiment of the present invention includes various components other than those described above, but is not the main focus of the present invention, and a description thereof will be omitted.
[0015]
(2) Calculation method of correction amount Next, a calculation method of the correction amount will be described. In the present embodiment, three methods will be described as typical calculation methods of the correction amount (however, the present invention is not limited to the three calculation methods).
[0016]
(1) First correction amount calculation method FIG. 5 is a flowchart illustrating the first correction amount calculation method. In step S501, the image data is read from the storage device 103 and stored in the RAM. In step S502, decoding processing is performed on the read image data to obtain 8-bit RGB data.
[0017]
In step S503, the RGB values at the sampling points are read from the image data. The sampling point is a point extracted from the image data at a certain fixed rate as described in the image data 201 in FIG. 2A. is there). By taking sampling points in this way, it is not necessary to perform processing on the entire image data, and the processing speed can be increased.
[0018]
In step S504, luminance is calculated from the read RGB data values of the sampling points, and a luminance histogram is created. In step S505, a highlight point H0, a shadow point S0, and an average luminance Y0 of the image data are calculated from the created luminance histogram. The highlight point H0 is a portion having the highest luminance as described in the luminance histogram 203 shown in (a) of FIG. 2B. On the other hand, the shadow point S0 is a portion having the lowest luminance as described in the luminance histogram 203 shown in (a) of FIG. 2B.
[0019]
In step S506, ideal (corrected) highlight point H1, shadow point S1, and average luminance Y1 of the image data are obtained. These values are set so that the image data is preferably felt by human eyes, and the degree is empirically determined from the characteristics (luminance) of the image data.
[0020]
In step S507, each change amount is calculated using the correction amount calculation formula 205 in FIG. 2C. In step S508, the average value (AVG (ΔH, ΔS, ΔY)) of each change amount is calculated, and is set as the correction amount of this image data.
[0021]
As described above, by using the luminance histogram, the correction amount (AVG (ΔH, ΔS, ΔY)) of the image data can be calculated.
[0022]
(2) Second correction amount calculation method FIG. 6 is a flowchart illustrating the second correction amount calculation method. In step S601, the image data is read from the storage device 103 and stored in the RAM. In step S602, decoding processing is performed on the read image data to obtain 8-bit RGB data.
[0023]
In step S603, the RGB values at the sampling points are read from the image data. In step S504, an RGB value histogram is created from the read RGB data values at the sampling points.
[0024]
In step S605, a gamma value to be corrected for the RGB value is calculated using the RGB value histogram. The gamma value is a constant used in the gamma conversion formula 301 shown in (a) of FIG. 3A, and draws a curve for correcting RGB values like a gamma curve 302 of (b) of FIG. The correction using the gamma curve is a method generally used in correcting image data. The setting of the gamma value is set so that the image data is preferably perceived by human eyes, and the degree is determined empirically from the characteristics of the image data (the distribution of RGB values).
[0025]
In step S606, the correction amount Δγ is calculated using the correction amount calculation formula 303 in FIG. 3B. Thus, the correction amount (Δγ) can be calculated by obtaining the gamma value for correcting the image data.
[0026]
(3) Third Correction Amount Calculation Method FIG. 7 is a flowchart illustrating a third correction amount calculation method. In step S601, the image data is read from the storage device 103 and stored in the RAM. In step S702, decoding processing is performed on the read image data to obtain 8-bit RGB data.
[0027]
In step S703, the RGB values at the sampling points are read from the image data. In step S704, as in the case of FIG. 5, a luminance histogram is obtained, and an average saturation is also calculated. In step S605, a 3 × 3 matrix value to be applied to the RGB values of the image data is calculated from the luminance histogram and the average saturation (matrix 401 shown in FIG. 4A).
[0028]
As shown in the figure, image correction by multiplying a 3 × 3 matrix value 401 by an RGB value (R0, G0, B0) is generally performed, and each element value (a, b, c,... i) are empirically calculated from the features (luminance, saturation) of the image data.
[0029]
In step S706, a matrix operation is performed on the RGB values (R0, G0, B0) of each sampling point using the calculated matrix value 401 (matrix operation expression 402 in FIG. 4A), and the corrected Are obtained (R1, G1, B1). In step S707, the average of the RGB values (R0, G0, B0) and the average of the corrected RGB values (R1, G1, B1) of all the sampling points are obtained, and are shown in FIG. 4B. Using the correction amount calculation formula 403, the amount of change (ΔR, ΔG, ΔB) of each RGB value is calculated.
[0030]
In step S708, the average value of the change amounts ΔR, ΔG, and ΔB is calculated, and the calculated average value is used as the correction amount of the image data. By calculating the correction matrix in this manner, the correction amount (AVG (ΔR, ΔG, ΔB)) of the image data can be calculated.
[0031]
(3) Sorting Process Next, a sorting process executed based on the correction amount obtained in the above (2) will be described.
[0032]
FIG. 8 is a flowchart illustrating a process of sorting image data using a correction amount. In step S801, first, an image data group to be sorted is specified. In step S802, an integer N indicating the number of the image data in the designated image data group is initialized to zero.
[0033]
In step S803, the correction amount of the N-th image data is calculated by one of the processes in FIGS. In step S804, the value of N is increased by one. In step S805, it is determined whether the correction amount has been calculated for all the image data of the specified image data group. If the correction amounts have been calculated for all the image data, the process proceeds to step S806; otherwise, the process returns to step S803.
[0034]
Here, since whether or not the image data is “satisfactorily taken” depends on the magnitude of the correction amount, in step S806, the calculated correction amounts of all the image data are compared, and the image data is compared in ascending order of the correction amount. Is sorted. As a result, printing, display, and other output can be performed in the sorted order.
[0035]
As is apparent from the above description, by sorting the image data in ascending order of the correction amount, it is possible to easily find the image data that has been successfully captured (that is, the load of the work of extracting the image data to be output is reduced). It is possible to improve convenience when handling image data.
[0036]
[Second embodiment]
In the present embodiment, a method will be described in which a large amount of image data is classified into predetermined groups, and the image data that is best captured is automatically selected from each group and printed. Note that the system configuration and the like of the image data processing apparatus according to the present embodiment are the same as those of the above-described first embodiment, and a description thereof will be omitted.
[0037]
FIG. 9 is a flowchart illustrating the flow of the process according to the present embodiment. In step S901, a group of image data to be printed is specified. In step S802, each image data of the designated image data group is classified into the same scene using the similar image search (the process (1) in FIG. 10). The similar image search is a technique for examining the distribution of RGB values of image data and searching for an image captured in a similar scene. A detailed description of this technique will be omitted because it is directly related to the present invention.
[0038]
In step S902, the photographing date and time of the image group grouped by the similar image search is checked, and further grouping is performed for each image having the same (or close) photographing date and time (the process (2) in FIG. 10). This is a process for dividing image data that is shot in similar scenes but is shot at different locations (for example, when the same sea scene is on a different beach). As shown in FIG. 12, the information on the shooting date and time is described in the header information 1202 of the header portion of the image data 1101, and can be obtained by reading it.
[0039]
In step S904, the sort process described in the first embodiment is executed for each group of image groups for each group (process (3) in FIG. 10). In step S905, image data with the smallest correction amount is extracted for each group (process (4) in FIG. 10). In step S906, one piece of image data extracted for each group is printed.
[0040]
In this way, by classifying the image data and executing the sort processing based on the correction amount for each group, the image data that can be best captured for each group is automatically selected from the large amount of image data group. And printing can be executed.
[0041]
[Third Embodiment]
In the second embodiment, the method of printing only the image data that has been successfully photographed for each scene has been described. However, some users may want to print all image data in which a person is the subject. Therefore, in the present embodiment, only the image data in which a person other than a person is a subject is sorted out of a large amount of image data groups, and the image data in which a person is a subject is not subjected to the sorting process. A printing method will be described. Note that the system configuration and the like are the same as in the first embodiment, and a description thereof will be omitted.
[0042]
FIG. 12 is a view for explaining shooting information added as header information 1202 to the image data 1201. As shown in the figure, the header information 1202 describes various information at the time of shooting. A file format such as Exif corresponds to this. The shooting information includes information such as shooting date and time, shooting mode (auto mode, portrait mode, landscape mode, night view mode, etc.), flash ON / OFF, and the like. By looking at the shooting mode among them, it is possible to determine what the subject of the image data is.
[0043]
FIG. 11 is a flowchart illustrating a process of sorting only image data in which a subject other than a person is a subject. In step S1101, an image data group to be printed is specified. In step S1102, the shooting mode is read from the header information of each image data of the specified image data group.
[0044]
In step S1103, it is determined whether the shooting mode is the portrait mode. If the shooting mode is not the portrait mode, the process proceeds to step S1104. If the shooting mode is the portrait mode, the process proceeds to step S1106.
[0045]
In step S1104, grouping and sorting are performed as described in the second embodiment. In step S1105, image data with the smallest correction amount is extracted from each group. In step S1106, printing is performed.
[0046]
As described above, by using the photographing information and the sort processing based on the correction amount together, it is possible to print only appropriate image data. In other words, if the subject is not a person, the sorting process is performed on the classified groups, and only the image data that is best captured for each group is printed. If the subject is a person, the sorting process is performed. All without printing.
[0047]
In the present embodiment, the subject is determined using the photographing information. However, any method may be used, such as using face recognition processing.
[0048]
[Other embodiments]
The present invention can be applied to a system including a plurality of devices (for example, a host computer, an interface device, a reader, a printer, etc.), but may be a device including one device (for example, a copying machine, a facsimile machine, etc.). May be applied.
[0049]
Further, an object of the present invention is to provide a storage medium storing a program code of software for realizing the functions of the above-described embodiments to a system or an apparatus, and a computer (or CPU or MPU) of the system or apparatus to store the storage medium. It is needless to say that the present invention can also be achieved by reading and executing the program code stored in the program.
[0050]
In this case, the program code itself read from the storage medium realizes the function of the above-described embodiment, and the storage medium storing the program code constitutes the present invention.
[0051]
As a storage medium for supplying the program code, for example, a floppy (registered trademark) disk, hard disk, optical disk, magneto-optical disk, CD-ROM, CD-R, magnetic tape, nonvolatile memory card, ROM, or the like is used. be able to.
[0052]
When the computer executes the readout program code, not only the functions of the above-described embodiments are realized, but also an OS (Operating System) running on the computer based on the instruction of the program code. It goes without saying that a part or all of the actual processing is performed and the functions of the above-described embodiments are realized by the processing.
[0053]
Further, after the program code read from the storage medium is written into a memory provided on a function expansion board inserted into the computer or a function expansion unit connected to the computer, the function expansion is performed based on the instruction of the program code. It goes without saying that a CPU or the like provided in the board or the function expansion unit performs part or all of the actual processing, and the processing realizes the functions of the above-described embodiments.
[0054]
【The invention's effect】
As described above, according to the present invention, when a plurality of image data are sorted in the order of the image data which is "taken well", the image data to be output from the plurality of image data is extracted. Work load can be reduced.
[Brief description of the drawings]
FIG. 1 is a diagram showing a system configuration of an image data processing apparatus according to an embodiment of the present invention.
FIG. 2A is a diagram showing sampling points of image data.
FIG. 2B is a diagram showing a luminance histogram before and after correction.
FIG. 2C is a diagram showing a correction amount calculation formula in a first correction amount calculation method.
FIG. 3A is a diagram showing a gamma conversion equation and a gamma curve.
FIG. 3B is a diagram illustrating a correction amount calculation formula in a second correction amount calculation method.
FIG. 4 is a diagram showing a matrix operation expression and a correction amount calculation formula in a third correction amount calculation method.
FIG. 5 is a flowchart showing a flow of processing by a first correction amount calculation method in the image data processing device according to the first embodiment of the present invention.
FIG. 6 is a flowchart illustrating a flow of processing by a second correction amount calculation method in the image data processing device according to the first embodiment of the present invention.
FIG. 7 is a flowchart showing a flow of processing by a third correction amount calculation method in the image data processing device according to the first embodiment of the present invention.
FIG. 8 is a flowchart illustrating a flow of a sorting process in the image data processing device according to the first embodiment of the present invention.
FIG. 9 is a flowchart showing a flow of processing in an image data processing device according to a second embodiment of the present invention.
FIG. 10 is a conceptual diagram showing a flow of processing in an image data processing device according to a second embodiment of the present invention.
FIG. 11 is a flowchart showing a flow of processing in an image data processing device according to a third embodiment of the present invention.
FIG. 12 is a conceptual diagram illustrating header information of image data.

Claims (22)

An image data processing method for changing an order of a plurality of image data,
A correction step of correcting the image data,
A correction amount calculating step of calculating a correction amount based on the image data before being corrected by the correcting step and the corrected image data;
Changing the order of the calculated correction amounts in ascending order. An image data processing method for changing an output order of a plurality of output image data,
A correction step of correcting the image data,
A correction amount calculating step of calculating a correction amount based on the image data before being corrected by the correcting step and the corrected image data;
A changing step of changing an output order for outputting the plurality of image data in order of the calculated correction amount being small. An image data processing method for outputting predetermined image data from a plurality of image data,
A classifying step of classifying the plurality of image data into a plurality of image data groups;
A correction step of correcting a plurality of image data included in the image data group for each of the classified image data groups,
A correction amount calculating step of calculating a correction amount based on the image data before being corrected by the correcting step and the corrected image data;
Outputting an image data with the smallest calculated correction amount for each of the classified image data groups. The correction amount is:
Including any of a change amount of a highlight point, a change amount of a shadow point, and a change amount of an average luminance of the luminance histogram of the corrected image data with respect to the luminance histogram of the image data before the correction. The image data processing method according to claim 1, wherein: The correction amount is:
4. The image data processing method according to claim 1, wherein the image data is a gamma value when the image data is gamma-corrected in the correction step. The correction amount is:
4. The method according to claim 1, further comprising a change amount of the corrected RGB value with respect to the uncorrected RGB value when the RGB value of the image data is multiplied by a predetermined element value in the correcting step. The image data processing method according to any one of the above. 4. The image data processing method according to claim 3, wherein the classification step classifies the plurality of image data for each similar image. 4. The image data processing method according to claim 3, wherein the classifying step classifies the plurality of image data based on information at the time of shooting included in each of the image data. 9. The image data processing method according to claim 8, wherein the information at the time of shooting includes a shooting mode and a shooting date and time. The output step includes:
The image data processing method according to claim 9, further comprising outputting image data in which a photographing mode is a person mode among the image data classified in the classification step. An image data processing device for changing the order of a plurality of image data,
Correction means for correcting the image data,
Correction amount calculation means for calculating a correction amount based on the image data before being corrected by the correction means and the image data after the correction,
Changing means for changing the order of the calculated correction amounts in ascending order. An image data processing device that changes an output order of a plurality of image data to be output,
Correction means for correcting the image data,
Correction amount calculation means for calculating a correction amount based on the image data before being corrected by the correction means and the image data after the correction,
An image data processing apparatus comprising: a changing unit configured to change an output order for outputting the plurality of pieces of image data in ascending order of the calculated correction amount. An image data processing device that outputs predetermined image data from a plurality of image data,
Classification means for classifying the plurality of image data into a plurality of image data groups,
Correction means for correcting a plurality of image data included in the image data group for each of the classified image data groups;
Correction amount calculation means for calculating a correction amount based on the image data before being corrected by the correction means and the image data after the correction,
An image data processing apparatus comprising: an output unit that outputs image data having the smallest calculated correction amount for each of the classified image data groups. The correction amount is:
Including any of a change amount of a highlight point, a change amount of a shadow point, and a change amount of an average luminance of the luminance histogram of the corrected image data with respect to the luminance histogram of the image data before the correction. The image data processing apparatus according to claim 11, wherein: The correction amount is:
14. The image data processing device according to claim 11, wherein the correction value is a gamma value when the image data is gamma-corrected. The correction amount is:
14. The correction method according to claim 11, wherein the correction unit includes a change amount of the corrected RGB value with respect to the uncorrected RGB value when the RGB value of the image data is multiplied by a predetermined element value. An image data processing device according to any one of the above. 14. The image data processing apparatus according to claim 13, wherein the classification unit classifies the plurality of image data for each similar image. 14. The image data processing apparatus according to claim 13, wherein the classification unit classifies the plurality of image data based on information at the time of shooting included in each of the image data. 19. The image data processing apparatus according to claim 18, wherein the information at the time of shooting includes a shooting mode and a shooting date and time. The output means,
20. The image data processing apparatus according to claim 19, wherein, of the image data classified by the classification unit, image data in a shooting mode of a person mode is further output. A control program for causing a computer to implement the image data processing method according to any one of claims 1 to 10. A recording medium storing a control program for causing a computer to implement the image data processing method according to claim 1.

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