JP2006172358A - Method and apparatus for image formation - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To perform high grade processing such as red-eye correction and to appeal that and make an image output client or the like recognize that when performing image output. <P>SOLUTION: The above problem is solved by creating a moving image which changes from an image formed by applying only a first image processing to an image formed by applying the first and a second image processings and outputting a moving image file in addition to the image to become a product in image formation for performing first basic image processing and second high grade image processing. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  In the technical field of image formation in which image processing is performed on an optically photographed image and output as an image file, the present invention performs image processing when performing high-quality image processing such as red-eye correction processing and outputting an image. The present invention relates to an image forming method and an image forming apparatus that enable a customer who orders the output of the above to recognize that the output image has been subjected to high-quality image processing.

In recent years, an image recorded on a film is photoelectrically read, the read image is converted into a digital signal, and then subjected to various image processing to obtain image data for recording. By recording light modulated in accordance with the image data, Digital photo printers that expose photosensitive materials and output them as prints have been put into practical use.
In a digital photo printer, an image photographed on a film is photoelectrically read, and the image is processed as digital image data to perform image processing or exposure of a photosensitive material. Therefore, a print can be created not only from an image shot on a film but also from an image (image data) shot by a digital camera or the like.

Digital photo printers not only output images as prints, but also output image data as image files to recording media such as CD-Rs and DVDs, or provide them to customers, or via communication networks such as the Internet. Can also be provided.
In addition to simply outputting image data, a so-called photo movie service is also provided in which images are sequentially displayed as in a slide show, and images are reproduced while being enlarged / reduced or moved.

As described above, since a digital photo printer handles an image as digital image data, image processing (image correction and adjustment) can be performed by processing the image data.
Therefore, compared to conventional analog exposure printers (printers that expose photosensitive materials (printing paper) with the projection light of the film), the color / density correction, gradation correction, saturation correction, and sharpness are much more flexible. Image processing such as processing, dodging processing (adding a dodging effect by adjusting the image dynamic range while maintaining intermediate gradation), for example, overexposure, underexposure, backlight scene, high contrast scene, etc. Even if it exists, it is possible to stably reproduce high-quality images.

  Furthermore, with digital image processing, red-eye correction (correction of red-eye phenomenon caused by flash photography), peripheral light reduction correction (correction of density unevenness due to peripheral light reduction of the photographing lens), aberration correction (according to the aberration of the photographing lens) Distortion correction), scratch removal processing (correction of defective pixels due to scratches on the film or taking lens, attached dust, etc.), etc., printers with analog exposure require very advanced technology from the operator, or are extremely difficult or Image processing that is substantially impossible can also be performed by processing image data.

By performing the color / density correction, gradation correction, saturation correction, sharpness processing, and dodging processing, a sufficiently high quality image can be obtained in terms of photographic image quality. That is, an image as a product can be finished by performing only these image processes.
On the other hand, red-eye correction, peripheral light reduction correction, aberration correction, scratch-removal processing, and the like are processes for correcting image defects, which are different from so-called photographic image quality.
Here, each image processing such as color / density correction can set image processing conditions and the like by analyzing low-resolution image data such as so-called pre-scan data and thinned images, and the amount of calculation. Therefore, the processing can be performed in a relatively short time. On the other hand, red-eye correction and scratch removal processing require analysis with high-resolution image data corresponding to the output, and also require a complicated and large amount of computation. In addition, aberration correction and peripheral dimming correction also require information corresponding to the taking lens, and require a complicated and large amount of computation.

  In other words, red-eye correction and peripheral light reduction correction can be said to be high-quality image processing compared to normal image processing that corrects color, density, gradation, etc. to finish a proper image. By performing these processes, the advantages of digital exposure can be fully exerted, and so-called high-quality images corrected for image defects can be output. And an advanced system is required.

However, the customer (photographer who created the photo print) appreciates the finished image as a product. Even if high-quality image processing such as red-eye correction is performed, the customer usually There is no knowledge of the processing or the effect.
Therefore, even if processing time is taken and high-quality processing is performed using an advanced image processing system, and a higher quality image than a general lab system or processing system is finished, it is appealed to the customer. It is very difficult to get an evaluation.

  As a method for solving such a problem, Patent Document 1 discloses that an image is selected from one item ordered by a customer, and this image is digitally enhanced (qualitative improvement / enhancement). And a method for outputting a non-enhanced image and a non-enhanced image.

JP 2003-205660 A

According to this method, it is possible to have a customer recognize and evaluate that a high-quality image has been output by image processing.
However, this method cannot sufficiently show the effects of high-quality processing such as red-eye correction, scratch cancellation processing, peripheral light reduction correction, and aberration correction, and the appeal of the effect of high-quality processing is not sufficient. No.

  An object of the present invention is to solve the above-described problems of the prior art, and to high-quality images that are taken on a photographic film or taken with a digital camera or the like, such as red-eye correction, which requires time and effort. When image processing is performed and the image is output, the customer who ordered the image can be surely appealed and recognized that the image has been output by performing high-quality image processing. It is an object to provide an image forming method capable of outputting an image with high performance and amusement, and an image forming apparatus for performing the image forming method.

  In order to achieve the above object, an image forming method of the present invention performs first image processing and second image processing on one entire image composed of a plurality of optically photographed images. The still image is output as an image file, and for one or more target images selected from the one case, the first image processing and the second image are performed from the image subjected to only the first image processing. At least one of a moving image that changes to an image subjected to image processing and a moving image that changes from an image subjected to the first image processing and the second image processing to an image subjected to only the first image processing is created Thus, an image forming method is provided which outputs the image as a moving image file.

  In addition, the image forming apparatus of the present invention is configured to acquire an image for each case composed of a plurality of optically photographed images, and to perform first image processing and second image processing on the acquired images. Processing means for outputting as a still image file; and selection means for selecting one or more images from the one case as target images; and the processing means for the target image selected by the selection means An image that has undergone only the first image processing is also generated, and for the target image selected by the selection unit, the first image processing and the second image processing are performed from the image that has undergone only the first image processing. A moving image that changes to an image that has been subjected to the first image processing and an image that has undergone only the first image processing from the image that has undergone the first image processing and the second image processing. As a file To provide an image forming apparatus characterized by having a moving image creating means for.

In such an image forming method and image forming apparatus of the present invention, the moving image is an image obtained by performing only the first image processing, and an image subjected to the first image processing and the second image processing. The moving image that changes and the image that has undergone the first image processing and the second image processing are at least one of the moving image that gradually changes to an image that has undergone only the first image processing. It is preferable that the second image is obtained from the time when the moving image is formed by performing only the first image processing to the time when the image subjected to the first image processing and the second image processing is formed. The moving image is preferably shown as the processing progresses.
The first image processing is preferably image enlargement or reduction, gradation correction, color / density correction, saturation correction, sharpness processing, and dodging processing, and the second image The processing is preferably image processing for analyzing information related to an image and correcting the image defect only when it is detected that the image has an image defect as a result. It is preferable that the information related to the image is at least one of an image and photographing information, and the second image processing includes red-eye correction, image defect correction, aberration correction caused by the photographing lens, and photographing. Preferably, it is at least one of the peripheral dimming correction due to the lens.

By having the above-described configuration, the present invention is caused by red-eye correction, correction of image (pixel) defect due to dust and film or lens scratches attached to the film or lens, and aberration of the lens that captured the image. Request image output when performing high-quality image processing that takes time and effort, such as correcting image distortion and correcting the peripheral density reduction caused by the peripheral light reduction of the lens that captured the image. It is possible for the customer to recognize that the image has been output by performing such high-quality image processing. Moreover, since a moving image file is output and a change from an image not subjected to high-quality processing to a processed image is displayed as a moving image, the appeal is very high, and the hobby and entertainment are also high.
Therefore, by using the present invention, high quality processing and work such as red-eye correction are surely appealed to and recognized by the customer, and high added value and high quality processing of the image (product) are achieved. Differentiation from images that are not performed, differentiation from other stores in a lab store, maintenance of prices for other stores, acquisition and securing of customers, and the like can be achieved.

  Hereinafter, an image forming method and an image forming apparatus of the present invention will be described in detail based on preferred embodiments shown in the accompanying drawings.

FIG. 1 is a flowchart showing an example of an image forming method according to the present invention.
FIG. 1 shows an example of a processing flow when the image forming method of the present invention is carried out by the above-described digital photo printer. An image (image data) is acquired and output as an output image (image data). The input device 10 of the digital photo printer.

As an example, the input device 10 photoelectrically reads an image photographed on a photographic film by a scanner to obtain an image (image data), and / or an imaging device such as a digital camera or a mobile phone with a photographing function, SmartMedia ^TM and PC card ^TM like storage medium that stores an image captured by the imaging device, various kinds of communication network or the like of a personal computer or a print order receiving terminal or the like is connected, an image captured by the imaging device ( Image data).
That is, even if the input device 10 has a function corresponding only to image formation from photographic film, it corresponds only to image formation obtained by acquiring an image (that is, image data) taken by a digital camera or the like. Even if it has a function, it may have both functions.

  The input device 10 that has acquired the image displays the verification image (finished simulation image) on the display to perform the verification, and after the verification is completed, performs necessary image processing (basic processing and high-quality processing described later). , And output as an output image (image data).

The output destination of the image created by the input device 10 is not particularly limited. For example, a recording unit that records an image on a storage medium such as a CD-R or a DVD is exemplified. Alternatively, the image may be output to a predetermined server, an order reception machine installed in a street or a lab shop, a communication terminal installed in a lab shop, or the like using a communication means such as the Internet.
Further, the input device 10 may output an image of a product image other than a promotional video to be described later to a printer that outputs a print (hard copy) obtained by reproducing the image. The printer is not particularly limited, and all known printers such as a photographic printer that reproduces an image on a photographic paper, an inkjet printer, an electrophotographic printer, a printer that uses a thermal recording medium, and a printer that uses a photosensitive thermal recording medium can be used. Is available.

  The present invention forms a proportion movie for the purpose of prosecution of the effect of high quality processing from among one image in the output of one image that performs image processing (basic processing and high quality processing) as described above. One or a plurality of images (frames) for promotion are selected as promotion target images, and only the basic processing is added to the selected promotion target images in addition to the output images (product images) subjected to basic processing and high-quality processing. A moving image that changes (and / or vice versa) from an image subjected to processing to an image subjected to high-quality processing is created, and this moving image file is also output.

The basic processing (first image processing) is a basic processing performed to output an image having an appropriate color / density (tone reproduction, color reproduction), image structure (sharpness, graininess), and the like. Image processing. By performing this basic processing, the image is completed in terms of photographic image quality, and becomes a completed image corresponding to image output such as normal print output without high-quality processing. In the illustrated example, as an example, enlargement or reduction of the image (electronic scaling process), gradation correction, color / density correction, saturation correction, sharpness processing, and dodging processing (maintaining the intermediate gradation of the image) , Compression or expansion of the image density dynamic range).
On the other hand, high-quality processing (second image processing) is image processing for correcting only an image having a defect in order to correct an image defect. More preferably, it is image processing for correcting only an image detected to have a defect as a result of analyzing information on the image. Specifically, red-eye correction (red-eye correction) caused by flash photography, foreign matter adhering to photographic film or taking lens, and image (pixel) defect caused by photographic film or taking lens scratches (dust removal) Processing), correction of image distortion caused by aberration of the photographing lens (lens aberration correction), and correction of peripheral density decrease caused by peripheral light reduction of the photographing lens (peripheral light reduction correction).

In the present invention, information relating to an image refers to the image (image data) itself and imaging information of the image.
The shooting information specifically refers to the presence or absence of flash emission at the time of shooting, the information of the camera (lens) that shot the image, the information of the photographic film that shot the image, the information of the aperture at the time of shooting, the shutter speed, etc. Information etc. are illustrated. Shooting information may be acquired from magnetic information recorded on a film if the image is formed from an APS film, for example, and acquired from information recorded in an image file if the image is captured by a digital camera or the like. do it.

Hereinafter, an example of image formation according to the present invention shown in FIG. 1 will be described using a case where red-eye correction is performed as high-quality processing as an example.
Further, in the following description, for convenience, an image that has undergone both basic processing and high-quality processing (including a case in which only analysis of information about the image is performed and no correction is performed) An image that has undergone only processing is defined as an unprocessed image, and a moving image that changes between the unprocessed image and the processed image is defined as a promotion movie.

The example shown in FIG. 1A is an example in which a promotion target image that is an image for creating a promotion video is selected by an operator (manual selection of a promotion target image).
When the input device 10 acquires one image (image data) as described above (or during the acquisition of one image), the input device 10 displays the verification image on the display and causes the operator to execute the verification. . The test image is subjected to image processing according to basic processing applied to the output image. In addition, the image processing conditions of the basic process are set by analyzing the original image of the test image as an example, and when color / density adjustment is performed by the test, the image processing of the basic process is performed accordingly. Conditions are also changed.
In the illustrated example, the test screen also serves as a selection screen for the promotion target image, and uses a known means such as GUI (Graphical User Interface) (the same applies to other selections to be performed below). An image is indicated. In response to this, the input device 10 selects the instructed image as the promotion target image. The selection (input instruction) of the promotion target image may be one frame or a plurality of frames. Moreover, the operator may select the promotion target image using, for example, an automatic selection criterion described later.

  In the case where a promotion target image is not selected in one process, a promotion video is not created in this case. When the test is not performed, an image (preferably an image similar to the test image) is displayed for selection of the promotion target image.

In the illustrated example, the test image may be displayed in the same manner as a normal digital photo printer. In other words, when an image is acquired by reading a film with a scanner, it is performed with an image (pre-scan data) obtained by pre-scanning, which is performed prior to fine scanning, which is image reading for output, and with a digital camera or the like. In the case of a photographed image, the acquired image may be thinned (or reduced).
Further, when the film is read by the scanner, the fine scan may be performed after completion of the test, or may be performed in conjunction with the pre-scan.

Once the examination and promotion target images are selected, the basic processing is sequentially performed on the images of each frame. In addition, this image is an image corresponding to output, and is an image by fine scan (fine scan data) if the print is created from photographic film, and a captured image (photographed image data) if the image is by a digital camera or the like. It is.
In the illustrated example, as described above, enlargement or reduction of an image, gradation correction, color / density correction, saturation correction, sharpness processing, and dodging processing are performed as basic processing.
Any of these image processing may be performed by a known method.

Next, red-eye correction (high quality processing) is sequentially performed on the image subjected to the basic processing. In addition, the image selected as the promotion target image also sends the unprocessed image (the image that has undergone only the basic processing) to the storage means in parallel with the red-eye correction.
At this point, if the shooting information can be acquired and if it is found from the analysis result of the shooting information that the image is not a stroboscopic shot, the image does not have red eyes (hereinafter referred to as a non-red-eye image). At this point, the red-eye correction is finished, and the processed image is subjected to basic processing and red-eye correction (high-quality processing) without performing image correction.

There are no particular limitations on the red-eye correction method, and various known methods can be used. The following method is illustrated as a suitable example.
In this red-eye correction, first, a red-eye candidate (a region that may be red-eye) is detected from an image for which basic processing has been completed, and position information (center coordinate position information), region information, and number of red-eye candidates are detected. Get information and more.
Therefore, the image in which the red-eye candidate is not detected by the detection of the red-eye candidate is regarded as a non-red-eye image, and the red-eye correction is completed at this point, and the basic process and the red-eye correction are performed without correcting the image The finished image.

  As an example, if a person is photographed in a scene having three red lamps in the background as shown in FIG. 2 and an image (scene) in which this person has a red-eye phenomenon, a, b, And c, and regions indicated by d and e corresponding to red eyes are detected as red eye candidates.

There are no particular limitations on the method for detecting a red-eye candidate, and various known methods can be used.
As an example, using a red-eye color information (red-eye is red) and shape information (red-eye is round), a circular region having a red hue and a predetermined number of pixels or more is extracted, and a large number of red-eye images are obtained in advance. Use the red eye degree (how much red-eye color) and circularity (how round it is) set from the sample, and the area where the red eye degree and circularity exceed the threshold values as red eye candidates that may be red eyes The method of detecting is illustrated.

Next, using the detection result of the red eye candidate (for example, the position information), face detection is performed in a peripheral region including the detected red eye candidate.
For example, in the example illustrated in FIG. 2, face detection is sequentially performed in a predetermined region including each red-eye candidate corresponding to each of the red-eye candidates a, b, c, d, and e. Therefore, for example, a region surrounded by a dotted line is detected as the face region, and information that the red-eye candidates d and e are red-eye candidates included in the face region, or information on the detected face region is obtained.

There are no particular limitations on the face detection method, and various known methods can be used.
As a preferred example, a method of performing face detection by template matching using an average face image so-called face template (hereinafter referred to as a face template) created in advance from a large number of face image samples is performed.
In this method, as an example, a face template (or target image) is displayed on the top and bottom as shown in FIG. 3A according to the orientation of the camera at the time of shooting such as vertical position (vertical shooting) / horizontal position (horizontal shooting). The image is rotated in the left-right direction (rotated from 0 ° → 90 ° → 180 ° → 270 ° on the image plane) to change the face direction, and according to the size (resolution) of the face in the image, FIG. ), The face size of the face template (same as above) is changed (enlargement / reduction = resolution conversion), a face template of a combination of various face orientations and face sizes, a face candidate area in the image, The face detection is performed by sequentially performing matching (confirmation of matching).
Instead of rotating and enlarging / reducing the face template, a rotated face template or an enlarged / reduced face template may be created in advance, and matching may be performed using the template. Further, the face candidate area may be detected by means such as skin color extraction or contour extraction.

The face detection method is not limited to this template matching method.
For example, face detection using a learning method is also preferably exemplified. In this method, a large number of facial images and non-facial images are prepared, the respective feature amounts are extracted, and a face or non-face is separated from the result using an appropriately selected learning method. Perform prior learning to calculate functions and thresholds. When performing face detection, the feature amount is extracted from the symmetric image in the same manner as in the pre-learning, and the face or non-face is determined using the function and threshold obtained in the pre-learning, Face detection by a learning method that performs face detection is also suitable.
Furthermore, face detection by shape recognition by edge (contour) extraction and edge direction extraction disclosed in JP-A-8-184925 and JP-A-9-138471, face by color extraction such as skin color extraction or black extraction Various methods exemplified as face detection methods other than matching using face templates in Patent Documents 1 to 3 described above can also be used.

In this way, using the detection result of the red-eye candidate and the information of the red-eye candidate whose face has been detected, the red-eye candidate whose face can be detected around is identified as a red-eye.
Therefore, after performing face detection, an image in which no face is detected around all red-eye candidates is regarded as a non-red-eye image. At this point, the red-eye correction is completed, and the basic processing and red-eye correction are not performed. It is assumed that the processed image has been corrected.

When the red eye is specified in this manner, the specified red eye region is subjected to image processing, red eye correction is performed, and a processed image having undergone basic processing and red eye correction is obtained.
There are no particular limitations on the red-eye correction method, and various known methods can be used. For example, processing to correct red-eye by controlling the saturation, brightness, hue, etc. of the red-eye area according to the image features such as red-eye and the surroundings of the red-eye (may include the periphery of the face), or simply the color of the red-eye area The correction process etc. which convert black into black are illustrated.

In this way, the red-eye candidate detection is performed first, then the face detection is performed only around the detected red-eye candidate, and the red-eye candidate whose face can be detected in the vicinity is identified as the red-eye, thereby reducing the time for red-eye detection. It can be greatly shortened.
That is, as described above, red-eye detection including face detection is a time-consuming process, but in conventional red-eye detection, after face detection, red-eye detection is performed within the detected face area. Therefore, face detection is performed even in a region where no red eye exists, and as a result, it takes a very long time to detect the face. On the other hand, after detecting a red eye candidate in this way, by performing face detection only in a predetermined region including the red eye candidate, there is no useless face detection in a region where no red eye exists, and in red eye detection, The time required for face detection can be greatly reduced.

Note that the red-eye correction method (red-eye correction algorithm) is not limited to this method, and a normal red-eye correction method in which red-eye detection is performed after face detection can also be used. Other known red-eye correction methods are also available. All correction methods are available.
Further, the same red-eye correction method is performed in all the apparatuses, and the red-eye correction method may be executed in one or more apparatuses or in all apparatuses.

As described above, in the image formation shown in FIG. 1A, the input device 10 sequentially performs red-eye correction on an image (frame) that has undergone basic processing and outputs it as a product (still image file). Processed image (image data thereof).
Here, the image selected as the promotion target image stores an unprocessed image in the storage means. This unprocessed image is read from the storage means at a predetermined timing, and is supplied to the promotion process as a processed image for creating a promotion video.
Further, the processed image of the image selected as the promotion target image (or the image being red-eye corrected) is also supplied to the promotion processing when the red-eye correction is completed, for example.

When the processed image and the unprocessed image of the promotion target image are supplied to the promotion process, the input device 10 performs the promotion process and forms a promotion video.
This will be described in detail later.

In the example shown in FIG. 1A, the promotion target image is selected in accordance with an input instruction by an operator or the like. However, the present invention is not limited to this. (Data) and photographing information may be automatically performed by the apparatus (automatic selection of promotion target images).
Hereinafter, this automatic selection will be described with reference to FIG.

  In this example, in the input device 10, the image of one image is stored in the same manner as in the previous example, except that the operator does not instruct the promotion target image (manual selection of the promotion target image) at the time of verification or the like. Acquire and display / verify the test image.

When the input device 10 completes the verification, each image is sequentially subjected to basic processing, and then subjected to red-eye correction (high quality processing) to be processed as an image (its image data) to be reproduced on the product print. To do.
In addition to the red-eye correction, unprocessed images that have undergone only basic processing are sequentially sent to and stored in the storage means.

It should be noted that, at this point in time, an image that is found not to be a flash photography from the photographing information may be a processed image without performing red-eye correction, as in the previous example. In addition, an unprocessed image that is not a flash image may not be stored in the storage unit. If the shooting information cannot be acquired, and if it is not possible to determine whether or not the flash shooting is based on the shooting information, red eye correction is performed on all the basic processed images, and the unprocessed image is stored in the storage unit. .
That is, in this example, all the unprocessed images of one case, or all of the unprocessed images that can be determined to be strobe shooting from the shooting information, are stored in the storage unit.

Red-eye correction is performed as before.
That is, first, an image that was found not to be a flash photography from the shooting information is a non-red-eye image. At this point, the red-eye correction is completed and the basic process and the red-eye correction are performed without performing the correction. The finished image. For other images, first, red-eye candidates are detected, then face detection is performed around the red-eye candidates, red-eye candidates that have detected faces in the vicinity are determined as red-eye, correction is performed, basic processing and The processed image is subjected to red-eye correction. Also, images for which red-eye candidates could not be detected and images whose faces could not be detected in the vicinity of red-eye candidates are not red-eye images. The processed image is processed and red-eye corrected.

When the red-eye correction is completed, next, for each image, an optimum image as a promotion video is determined, and a promotion target image is selected.
The optimal image for the promotional video is determined using the above-mentioned red-eye detection result. For example, the red-eye size (face size), whether the red-eye exists near the center of the image (main image portion), red-eye Reliability (color and saturation), whether or not a specific person with red eyes is captured in one image (whether or not a red-eye person is an important person), reliability of red-eye detection (red-eye candidate detection, face) One or a plurality of factors are comprehensively determined from various factors such as the height of a determination value in detection and the like, and an image that is considered to have a great appeal effect of red-eye correction is determined and selected as a promotion target image. That is, the processed image and the unprocessed image are compared, and one image or a plurality of images that can clearly know that the red-eye correction has been performed are selected as the promotion target image.

In the illustrated example, at the time when the red-eye correction is completed, the suitability as a promotion video is evaluated for each image in accordance with a predetermined discrimination criterion using the detection result of the red-eye in the red-eye correction sequentially. When the evaluation is completed, the image with the highest evaluation (one frame) is selected as the promotion target image. Or you may select the predetermined number of images with high evaluation as a promotion object image.
As an example, on the processed image (product image), it is necessary to have a red eye of a predetermined size (number of pixels) or more, and in an image that satisfies the essential condition, from the image center (screen center) of the largest size red eye Evaluate suitability as a promotional video by distance. That is, an image having red eyes of a predetermined size or more and having the maximum size red eye in the image closest to the center of the image is determined as the optimum image and selected as the promotion target image.

The automatic selection method of the promotion target images is not limited to this, and a method of selecting a predetermined number of optimum images by comparing each image individually is also suitable.
That is, when the basic processing of the first frame image is completed, the unprocessed image is stored in the storage unit, the red-eye correction is performed on the image, and the red-eye detection result is similarly used as the promotion image. The evaluation result is sent to the storage means. When the basic processing of the second frame image is completed, similarly, the unprocessed image is stored in the storage means, red-eye correction is performed, evaluation is performed, and the result is sent to the storage means. The storage means compares the evaluations of the images in the first frame and the second frame, leaves only the unprocessed image with higher evaluation, and deletes the other. Further, the third frame image is similarly stored in the storage unit, red-eye corrected, and evaluated, and sent to the storage unit. The storage unit evaluates the stored image and the third frame image. In comparison, only the unprocessed image with high evaluation is left as a candidate image, and thereafter, the fourth frame, the fifth frame,... Are processed in the same manner, and all the one image is processed. The image of the unprocessed image remaining in the storage means is selected as the promotion target image.

  Here, in the aspect in which the promotion target image is automatically selected, for example, in the case of the above-described example, there is no red-eye image of a predetermined size or more on the processed image. If there is no image satisfying the minimum standard), the effect of the promotional video cannot be obtained sufficiently, so it is preferable not to create the promotional video.

In the present invention, the automatic selection of the promotion target image is not limited to a configuration in which an optimal image is determined and selected.
For example, a predetermined number of images (frames) in which red eyes are first detected may be selected as promotion target images. Or, similarly, for each image, evaluation as a promotion target image was performed at the time when red-eye correction was completed, and an image whose evaluation exceeded a threshold value set as appropriate was selected as a promotion target image, and a predetermined number could be selected. The selection may be terminated at that time.
Further, for selection of the promotion target image, some discrimination criteria may be prepared and selectable, and / or discrimination criteria may be arbitrarily set.

When the promotion handling image is determined in this way, the unprocessed image of the promotion target image is sent from the storage means to the promotion process. In addition, after sending a required unprocessed image to a promotion process, you may delete the unnecessary unprocessed image which remains in a memory | storage means.
Further, the processed image of the promotion target image (or the image during the red-eye correction process) is also sent to the promotion process. Therefore, when performing automatic selection, it is necessary to store images other than images that are determined not to be promotion target images.

In both the manual selection and the automatic selection of the promotion target image, the input device 10 performs the promotion process when the processed image and the unprocessed image of the promotion target image are supplied to the promotion process as described above. A promotion video that is a video that changes from a processed image to a processed image is formed.
In the present invention, the promotion video is not limited to a video that changes from an unprocessed image to a processed image, and may be a video that changes from a processed image to an unprocessed image. It may be a moving image that changes to an image and becomes an unprocessed image again, or a moving image that repeats each change a plurality of times.

There are no particular limitations on the promotional video, and various types of video that change between an unprocessed image and a processed image are exemplified.
As a preferred example, a moving image that gradually changes from an unprocessed image and becomes a processed image is illustrated. For example, this moving image may be created by gradually changing the addition rate (total of 100%) of an unprocessed image and a processed image. In the image shown in FIG. 2, for example, as schematically shown in FIGS. 4A and 4B, an image in which the addition rate of the unprocessed image is initially 100% and the addition rate of the processed image is 0%. Gradually, the addition rate of the unprocessed image of the image is decreased and the addition rate of the processed image is increased. Finally, the addition rate of the processed image is 100% and the addition rate of the unprocessed image is 0%. The moving image which becomes the image of is illustrated.
Note that the change in the addition rate may be continuous as shown in FIG. 4A or may be stepwise.

As another preferred example, in addition to the processed image and the unprocessed image, an image that is undergoing a red-eye correction process (high-quality process) is used, and an unprocessed image is processed depending on the processing process of the red-eye correction (high-quality process). A moving image that changes from an image to a processed image is also exemplified.
As described above, the red-eye correction in the illustrated example first detects a red-eye candidate, performs face detection around the detected red-eye candidate, and uses a red-eye candidate whose face can be detected in the vicinity as a red-eye image. Correct the red eye.
Similarly, in the image shown in FIG. 2, as schematically shown in FIG. 5, the red-eye candidate is changed from the unprocessed image according to the red-eye correction process, and then the red-eye candidate is changed. It is also preferable to use a promotional video that creates a video that changes to an image for which face detection has been completed, and finally changes to a processed image that has been corrected for red eyes.

The input device 10 may create both moving images of the gradually changing moving image illustrated in FIG. 4 and the moving image corresponding to the processing process illustrated in FIG. 5 as a promotional moving image.
Moreover, you may enable it to select the moving image to produce.

Various messages may be combined as images with the promotional video. In addition, a message or BGM may be added as a voice to the promotional video, and both message image synthesis and voice addition may be performed.
The content of the message is not particularly limited. As an example, a message indicating that red-eye correction has been performed on this image, an appeal of the effect of red-eye correction (high-quality processing), information on frames (images) that have undergone other red-eye correction, lab stores For example, advertisements for stores, advertisements for digital photo printers and manufacturers, messages that combine these, and the like.
It is preferable to set a plurality of contents of the message in advance so that they can be selected, and it is also preferable to arbitrarily set the contents. Further, it is preferable that a message composition position, display / reproduction timing, font, character size, color, sound quality, and the like can be arbitrarily selected and set.

When the input device 10 creates a processed image of all the one image and a promotion video of the selected promotion target image in this way, the processed image (product image) is converted into a still image file, and on the other hand, The moving image is output as a moving image file to a recording means for recording data on a storage medium such as a CD-R or a DVD. Alternatively, using a communication means such as the Internet, the still image file and the moving image file are output to a predetermined server, an order acceptance machine installed in a street or a lab shop, a communication terminal installed in a lab shop, etc. . Alternatively, the still image file and the moving image file are output to both the recording means and the server. Note that the output destination of the still image file and the moving image file may be the same or different.
Further, in addition to the above output, the input device 10 may output the processed image to the above-mentioned printer for output of the print (hard copy), or output the processed image only to the printer, The video file of the promotional video may be output to a recording means or a server.

As is clear from the above description, according to the present invention, in image formation in which high-quality processing such as red-eye correction, dust scratch extinction, lens aberration correction, and peripheral light reduction correction is performed, one image from a film or a recording medium is used. A still image file of a processed image that has been subjected to high-quality processing by selecting an image from one related image such as an order order, and a video file of a promotion video that changes between an unprocessed image and a processed image Since the output is performed, it is possible to reliably appeal and recognize the implementation of the high-quality processing, which takes time and effort, and the effect thereof to the customer who is requested to create the image. In addition, since the effect of high quality processing can be appealed with a moving image, the appeal effect is very high, and the hobby and entertainment are also excellent.
Therefore, according to the present invention, the output image has a high added value, is differentiated from an image that is not subjected to high-quality processing, is differentiated from other stores in a lab store, the price is maintained for other stores, and customers are acquired and secured. Etc.

In the above example, the promotion target image is selected by manual selection (input instruction from the operator) or automatic selection (selection based on analysis of images and photographing information).
The present invention is not limited to this. For example, as an operation mode, a mode for selecting a promotion target image by manual selection (manual mode) and a mode for selecting a promotion target image by automatic selection (automatic mode) are set. It is also preferable that manual selection and automatic selection can be selected, such as enabling selection.

Automatic selection saves operator time and improves productivity, and even when a technically inexperienced operator operates the device, he selects the appropriate promotion target image and makes a suitable promotion video. Can be created stably.
On the other hand, in the manual selection, the effect of red-eye correction can be actually realized to the maximum, but an image that is not selected in the automatic selection can be selected as a promotion target image. For example, images of babies and infants with red eyes are images that customers find very unpleasant, and therefore promoting red-eye correction on these images can greatly enhance the effects of red-eye correction. Can appeal strongly. However, if there are many images that have a higher evaluation criterion than the image in which such a baby has red eyes, this image is not selected as a promotion target image. However, by performing manual selection, automatic selection is not performed, but an image with such a high appeal effect can be selected as a promotion target image, and a more effective promotional video can be created.

  Accordingly, by making it possible to switch between manual selection and automatic selection of the promotion target image by, for example, a method of providing the automatic mode and the manual mode as described above, the operability and productivity can be improved and the processing / operation versatility can be improved. And ensuring higher quality processing, the promotion video creation effect as described above can be further improved.

In the above example, red-eye correction is performed as high-quality processing (second image processing). As described above, in the present invention, various images other than red-eye correction are used as high-quality processing. Image processing that corrects a general defect can be used. Preferably, various image processing that corrects only an image in which a defect is detected as a result of analysis of information on the image can be used. As described above, scratch removal processing, lens aberration correction, peripheral light reduction correction, and the like are preferably exemplified.
Similar to the red-eye correction, each of these high-quality processes may be performed by a known method.

As an example of the flaw-removal processing method, a line segment that satisfies the condition is detected by edge detection, which is disclosed in Japanese Patent Laid-Open No. 2000-74846, and a defective portion caused by dust or scratches is detected using this line segment. , And a method of correcting a defect part by continuity with surrounding pixels or complementation using image data of a surrounding area, or a smoothing image and an original image disclosed in Japanese Patent Laid-Open No. 2000-92319 Examples include a method of detecting a defect candidate area caused by dust or scratches from the size of the difference, detecting a defect part from the feature of the candidate area such as a change in shape or color, and correcting the defect part as before. Is done.
In addition, when forming an image from an image taken on a photographic film, in addition to normal image reading of R (red), G (green), and B (blue), IR light (infrared light) is used. Using the IR light reading result and detecting the position of dust and scratches on the film using the IR light reading and scattering, the defect portion is detected as before. A method of correcting the error can also be suitably used.

In the case of performing scratch removal as a high-quality process, when automatically selecting a promotion target image as shown in FIG. 1B, the dust or scratch length, thickness is detected using the dust or scratch detection result. And one or more such as whether or not dust or scratches are on a main subject such as a face, whether or not the position of dust or scratches is close to the center of the image (main part of the image), etc. Therefore, it is only necessary to select one image or a plurality of images considered to have a great appeal effect of the scratch-removal process.
Furthermore, as a scratch removal method, when detecting the position of dust or scratches using IR light, an unprocessed image is used as an image that does not have an IR light image for an image that does not have an IR light image. You may handle as a processed image which did not memorize | store in a memory | storage means and also performed the high quality process, without performing a flaw removal process.

  Moreover, as a promotion moving image of the wound-removal process, a moving image that gradually changes from a processed image to an unprocessed image by changing the addition rate as illustrated in FIG. 4 is exemplified. Alternatively, as shown in FIG. 5, a moving image corresponding to the processing process, for example, a moving image showing only a defective portion due to dust or scratches detected from an unprocessed image, and then a moving image that changes to a processed image can also be used. It is.

  On the other hand, as a lens aberration correction method and a peripheral light attenuation correction method, for example, disclosed in Japanese Patent Application Laid-Open No. 11-225270, a camera type in which the lens characteristics of a camera are known and stored in advance and an image is taken ( A method of knowing the lens type) and performing lens aberration correction and / or peripheral dimming correction using corresponding lens characteristics is exemplified. If the lens type is image formation from an APS film, magnetic information is also read at the time of reading with a scanner, and this information is analyzed. On the other hand, image formation from an image taken with a digital camera or the like is possible. If there is, it may be detected by analyzing various images stored in the image film.

When performing lens aberration correction and peripheral dimming correction as high-quality processing, when automatically selecting a promotion target image as shown in FIG. 1B, the magnitude of aberration and dimming, aberration and dimming One image or a plurality of images that are considered to have a great appeal effect of lens aberration correction and peripheral light reduction correction may be selected by comprehensively judging the degree of conspicuousness. The magnitude of the aberration, dimming, and the degree of conspicuousness may be determined, for example, by detecting the change in aberration or dimming in a concentric circle that gradually increases around the center of the screen.
In addition, when performing lens aberration correction and peripheral light attenuation correction as high-quality processing, images that could not be distinguished from lens type and acquired lens characteristics are not subject to lens aberration correction and peripheral light attenuation correction. The unprocessed image may not be stored in the storage unit, and may be handled as an image that has been subjected to high quality processing without correction.

  As a promotional movie for correcting lens aberrations, a moving image that has been processed from a non-processed image with distortion gradually corrected, and as a promotional video for correcting for peripheral dimming, the peripheral density gradually decreases from an unprocessed image, or Each moving image is illustrated as an improved processed image.

In the present invention, the high-quality processing performed on the image is not limited to any one of red-eye correction, dust scratch cancellation processing, lens aberration correction, and peripheral light reduction correction, and two or more of these processings are performed. Of course, you may do this.
Furthermore, the high-quality processing to be performed may be appropriately selectable depending on a method for making a selection means, setting a work mode, or the like.

Further, depending on the combination of high-quality processing to be performed and a plurality of high-quality processing, it may be preferable to perform high-quality processing (or a part thereof) prior to basic processing.
In such a case, as schematically shown in FIG. 6 (shown in the example of automatically selecting the promotion target image), after performing the test, the basic processing and high-quality processing for obtaining the processed image are performed. In parallel, an unprocessed original image is stored in the storage means without performing basic processing, and the image selected as the promotion target image is subjected to basic processing after the corresponding original image is read from the storage means. Go to unprocessed images, and then perform promotion processing to create a promotional video.
In the promotion video, the change of the video corresponding to each high-quality process may be changed sequentially for each process, or may be changed simultaneously for a plurality of or all processes.

  Although the image forming method and the image forming apparatus of the present invention have been described in detail above, the present invention is not limited to the above-described embodiments, and various improvements and modifications can be made without departing from the gist of the present invention. Of course it is good.

(A) And (B) is a flowchart which shows the concept of an example of the image forming method of this invention. It is a conceptual diagram for demonstrating an example of the red eye correction method in this invention. (A) And (B) is a conceptual diagram for demonstrating an example of the red-eye correction method in this invention. (A) And (B) is a conceptual diagram for demonstrating an example of the promotion animation in this invention. It is a conceptual diagram for demonstrating another example of the promotion moving image in this invention. It is a flowchart which shows the concept of another example of the image forming method of this invention.

Explanation of symbols

  10 Input machine

Claims (8)

For all one image consisting of a plurality of optically photographed images, the first image processing and the second image processing are performed, and a still image is output as an image file.
In addition, for one or more target images selected from the one case, a moving image that changes from an image subjected to only the first image processing to an image subjected to the first image processing and the second image processing. And generating at least one of moving images that change from the image subjected to the first image processing and the second image processing to an image subjected to only the first image processing, and outputting the moving image as a moving image file. An image forming method.   The moving image is a moving image in which an image obtained by performing only the first image processing is gradually changed to an image subjected to the first image processing and the second image processing, and the first image processing and The image forming method according to claim 1, wherein the image that has undergone the second image processing is at least one of a moving image that gradually changes to an image that has undergone only the first image processing.   Progress of the second image processing until the moving image is formed with the first image processing and the second image processing from the image subjected to only the first image processing. The image forming method according to claim 1, wherein the image is a moving image shown in response to   The image formation according to claim 1, wherein the first image processing is image enlargement or reduction, gradation correction, color / density correction, saturation correction, sharpness processing, and dodging processing. Method.   5. The second image processing is image processing for analyzing information related to an image and correcting the image defect only when it is detected that the image has an image defect as a result. The image forming method according to any one of the above.   The image forming method according to claim 5, wherein the information related to the image is at least one of an image and photographing information.   7. The second image processing according to claim 5 or 6, wherein the second image processing is at least one of red-eye correction, image defect correction, aberration correction caused by a photographing lens, and peripheral light reduction correction caused by a photographing lens. Image forming method. Means for acquiring an image for each case consisting of a plurality of optically photographed images, processing means for applying the first image processing and the second image processing to the acquired image and outputting them as a still image file; Selecting means for selecting one or more images as target images from the one case,
The processing means also generates an image subjected to only the first image processing for the target image selected by the selection means, and further performs the first image processing for the target image selected by the selection means. First image processing from a moving image that changes from an image that has undergone only image processing to an image that has undergone first image processing and second image processing, and an image that has undergone the first image processing and second image processing An image forming apparatus comprising: a moving image creating unit that creates at least one of moving images that change to an image that has been subjected to image processing and outputs the moving image as a moving image file.

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