JP2009027563A - Image processor, image processing method, and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To enhance detection precision when a feature area is detected from a plurality of motion picture constituent images included in a motion picture. <P>SOLUTION: An image processor includes a feature area detection unit which detects the feature area from motion picture constituent images included in the motion picture by using a predetermined threshold, a feature area prediction unit which specifies a prediction area as an area wherein the feature area should be detected in a non-detection area as another motion picture constituent image of the detection image based upon the position of the feature area in the detection image as a motion picture constituent image where the feature area is detected, and a feature area detection control unit which makes the feature area detection unit detect the feature area from the prediction area of the non-detection image by using a threshold less than the predetermined threshold. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to an image processing device, an image processing method, and a program. The present invention particularly relates to an image processing apparatus and an image processing method for compressing an image, and a program for the image processing apparatus.

Among image blocks including a face detected in a moving image, an image encoding device that allocates and encodes an image block including eyes, a mouth, and the like by assigning more information bits than other image blocks is known. (For example, refer to Patent Document 1).
Japanese Patent No. 2828977

  However, according to the technique described in Patent Document 1, a frame in which an image block including a face, eyes, a mouth, and the like cannot be detected may occur depending on an imaging state of a subject. In this frame, a larger number of information bits cannot be assigned to image blocks including eyes, mouths, and the like than other image blocks.

  In order to solve the above-described problem, in the first embodiment of the present invention, an image processing device, wherein a feature region detecting unit detects a feature region from a moving image constituent image included in a moving image using a predetermined threshold value; Based on the position of the feature region in the detected image that is the moving image constituent image in which the feature region is detected, the prediction region that is the region in which the feature region is to be detected in the non-detected image that is the other moving image constituent image of the detected image A feature region prediction unit to be identified and a feature region detection control unit that causes the feature region detection unit to detect a feature region from a prediction region of a non-detected image using a threshold value lower than a predetermined threshold value.

  The feature region detection control unit causes the feature region detection unit to detect the feature region from the prediction region of the non-detected image using a threshold value lower than the predetermined threshold, and sets the predetermined threshold value from the region other than the prediction region of the non-detection image. The feature region detection unit may detect the feature region. The feature region prediction unit may specify the prediction region in the non-detected image based on the position of the feature region in each of the plurality of detected images preceding the non-detected image. The feature region prediction unit may specify the prediction region in the non-detected image based on the position of the feature region in each of the detected image before the non-detected image and the detected image after the non-detected image. The image processing apparatus may further include a motion vector acquisition unit that acquires a motion vector of a subject in the moving image, and the feature region prediction unit may specify a prediction region in the non-detected image based on the position and motion vector of the feature region in the detected image.

  A compressed video acquisition unit that acquires a compressed video including a motion vector; and a compressed video expansion unit that expands the video acquired by the compressed video acquisition unit. The feature region detection unit is expanded by the compressed video expansion unit. A feature region is detected from the moving image constituent image included in the moving image using the predetermined threshold, and the motion vector acquisition unit acquires a motion vector included in the moving image acquired by the compressed moving image acquisition unit. The prediction unit may specify the prediction region in the non-detected image included in the moving image expanded by the compressed moving image expansion unit based on the position of the feature region and the motion vector in the detected image.

  The compressed video acquisition unit acquires an MPEG video including a motion vector, the compressed video expansion unit expands the MPEG video acquired by the compressed video acquisition unit, and the feature region detection unit is expanded by the compressed video expansion unit The feature region may be detected from the moving image constituent image included in the MPEG moving image using the predetermined threshold, and the motion vector acquisition unit may acquire the motion vector included in the MPEG moving image acquired by the compressed moving image acquisition unit. An image dividing unit that divides each detected image and non-detected image into a feature region and a background region other than the feature region, and an encoding that encodes the feature region image and the background region image with different intensities. May be further included. An inclusion area specifying unit that specifies an inclusion area that includes the feature area specified in the detection image and the non-detection image, and a fixed value that fixes the pixel values of areas other than the inclusion area in each of the detection image and the non-detection image A coding unit, and the coding unit may compress the image of the inclusion region and the image of the region other than the inclusion region with different strengths.

  According to the second aspect of the present invention, there is provided an image processing method, a feature region detection stage for detecting a feature region from a movie constituent image included in a movie using a predetermined threshold, and a movie in which the feature region is detected. Based on the position of the feature region in the detection image that is the component image, a feature region prediction step that identifies a prediction region that is a region in which the feature region is to be detected in the non-detection image that is another moving image component image of the detection image; And a feature region detection control step of causing the feature region detection step to detect the feature region from a predicted region of the non-detected image using a threshold value lower than a predetermined threshold value.

  According to the third aspect of the present invention, there is provided a program for an image processing device that encodes an image, and the image processing device detects a feature region from a moving image constituent image included in the moving image using a predetermined threshold value. A feature region detection unit is a region in which a feature region is to be detected in a non-detected image that is another moving image constituent image based on the position of the feature region in the detected image that is a moving image constituent image in which the feature region is detected. A feature region prediction unit that identifies a certain prediction region and a feature region detection control unit that causes the feature region detection unit to detect a feature region from a prediction region of a non-detected image using a threshold value lower than a predetermined threshold value.

  It should be noted that the above summary of the invention does not enumerate all the necessary features of the present invention. In addition, a sub-combination of these feature groups can also be an invention.

  Hereinafter, the present invention will be described through embodiments of the invention, but the following embodiments do not limit the invention according to the claims. In addition, not all the combinations of features described in the embodiments are essential for the solving means of the invention.

  FIG. 1 shows an example of an image processing system 10 according to an embodiment. An object of the image processing system 10 is to reduce the amount of image data while maintaining a high quality image of a characteristic subject.

  The image processing system 10 includes a plurality of imaging devices 100a-c (hereinafter collectively referred to as imaging devices 100) that image the monitoring target space 150, and a plurality of image processing devices 120a-c (hereinafter referred to as image processing devices) that process images. 120), an image processing device 170, a communication network 110, and a plurality of display devices 180a-c (hereinafter collectively referred to as display device 180).

  The image processing device 120a is connected to the imaging device 100a. Further, the image processing device 120b is connected to the imaging device 100b. Further, the image processing device 120c is connected to the imaging device 100c. Note that the image processing device 170 and the display device 180 are provided in a space 160 different from the monitoring target space 150.

  Hereinafter, operations of the imaging device 100a, the image processing device 120a, the image processing device 170, and the display device 180a will be described. The imaging apparatus 100a MPEG-encodes a captured moving image obtained by imaging the monitoring target space 150, generates captured moving image data, and outputs the captured moving image data to the image processing apparatus 120a to which the imaging apparatus 100a is connected.

  The image processing device 120a acquires the captured moving image data generated by the imaging device 100a. The image processing device 120 decodes the captured moving image data acquired from the imaging device 100 to generate a captured moving image, and a plurality of features having different types of features such as a person 130 and a moving object 140 such as a vehicle from the generated captured moving image. Detect areas. Then, the image processing device 120a generates a plurality of feature area moving images by generating a moving image in which the characteristic region has a higher image quality than the other regions for each type of feature from the captured moving image. Further, the image processing apparatus 120a generates a background area moving image that is a moving image of a background area other than the characteristic area and has a lower image quality than the characteristic area moving image.

  Then, the image processing device 120a generates a plurality of feature region moving image data and background region moving image data by encoding the generated plurality of feature region moving images and background region moving images, respectively. At the same time, the image processing device 120a associates a plurality of characteristic area moving image data and background region moving image data obtained by encoding with each other and transmits them to the image processing device 170 through the communication network 110.

  The image processing device 170 acquires a plurality of feature region moving images and a background region moving image by decoding the associated plurality of feature region moving image data and background region moving image data received from the image processing device 120a, respectively. Then, the image processing apparatus 170 generates a single combined moving image by combining the plurality of feature region moving images and the background region moving image, and supplies the generated combined moving image to the display device 180a. The display device 180a displays the moving image supplied from the image processing device 170.

  The functions and operations of the imaging device 100b and the imaging device 100c are the same as the functions and operations of the imaging device 100a, except that the imaging moving image data is provided to the image processing device 120b and the image processing device 120c, respectively. The description is omitted. The functions and operations of the image processing device 120b and the image processing device 120c are the same as the functions and operations of the image processing device 120a, except that the captured moving image data is acquired from the imaging device 100b and the imaging device 100c, respectively. Good. Therefore, the description is omitted. Further, the image processing device 170 generates one moving image from the plurality of associated feature region moving image data and background region moving image data received from the imaging device 100b and the imaging device 100c, respectively, and displays each of the display devices 180b. And supplied to the display device 180c. In addition, the display device 180b and the display device 180c display each moving image supplied from the image processing device 170.

  When the image processing system 10 of the present embodiment is actually applied as a monitoring system, for example, there may be a case where a subject that is characteristic as a monitoring target such as a person or a moving object can be left with high image quality. In addition, the amount of moving image data may be reduced.

  FIG. 2 shows an example of a block configuration of the image processing apparatus 120. The image processing apparatus 120 includes a compressed moving image acquisition unit 201, a compressed moving image expansion unit 202, a feature region detection unit 203, an image division unit 204, and an image generation unit 205. In addition, the image processing apparatus 120 includes a motion vector acquisition unit 251, a feature region prediction unit 271, a feature region detection control unit 272, an inclusion region specifying unit 260, a fixed value unit 210, a reduction unit 220, and an encoding unit 230. An attachment processing unit 206 and an output unit 207.

  The inclusion area specifying unit 260 includes a plurality of inclusion area specifying sections 261a-261c (hereinafter collectively referred to as inclusion area specifying sections 261). Fixed value unit 210 includes a plurality of fixed value units 211a to 211c (hereinafter collectively referred to as fixed value unit 211). The reduction unit 220 includes a plurality of image quality reduction units 221a-d (hereinafter collectively referred to as image quality reduction units 221).

  The encoding unit 230 includes a background region moving image encoding unit 231a and a plurality of feature region moving image encoding units 231b-d (hereinafter collectively referred to as a feature region moving image encoding unit 231). The background area moving image encoding unit 231a and the feature area moving image encoding unit 231b-d may be collectively referred to as an encoding unit 231.

  The image quality reduction unit 221a and the background area moving image encoding unit 231a function as the compression unit 240a. Further, the image quality reduction unit 221b and the background area moving image encoding unit 231b function as the compression unit 240b. Similarly, the image quality reduction unit 221c and the background area moving image encoding unit 231c function as the compression unit 240c. The image quality reduction unit 221d and the background area moving image encoding unit 231d function as a compression unit 240d. The plurality of compression units 240a-d are collectively referred to as the compression unit 240.

  The compressed moving image acquisition unit 201 acquires a compressed moving image. Specifically, the compressed moving image acquisition unit 201 acquires encoded captured moving image data generated by the imaging device 100. For example, the compressed moving image acquisition unit 201 acquires an MPEG moving image including a motion vector. The compressed moving image decompression unit 202 restores the moving image acquired by the compressed moving image acquisition unit 201 and generates a plurality of moving image constituent images included in the moving image.

  Specifically, the compressed moving image decompression unit 202 decodes the captured moving image data acquired by the compressed moving image acquisition unit 201, and generates a plurality of moving image constituent images included in the moving image. For example, the compressed moving image expansion unit 202 expands the MPEG moving image acquired by the compressed moving image acquisition unit 201. The moving image composition image includes a frame image and a field image. The compressed moving image includes a motion vector of the subject in the moving image.

  The feature region detection unit 203 detects a feature region from a plurality of moving image constituent images included in the moving image. Specifically, the feature region detection unit 203 detects a plurality of feature regions having different types of features from a plurality of moving image constituent images included in a moving image that is an image. In addition, the feature region detection unit 203 detects a feature region from the moving image constituent image included in the moving image expanded by the compressed moving image expansion unit 202 using a predetermined threshold. For example, the feature region detection unit 203 detects a feature region from a moving image constituent image included in the MPEG moving image expanded by the compressed moving image expansion unit 202 using a predetermined threshold.

  Here, the feature area detection unit 203 uses the threshold value as a reference value when detecting the feature area. The feature area detection unit 203 can easily detect the feature area from the moving image constituent image by lowering the threshold value. For example, a degree of coincidence with a predetermined shape or color pattern related to the subject may be used as the threshold value.

  In this case, the predetermined subject is a person, a face, a car, or a license plate, but is not limited thereto. Moreover, you may change the brightness | luminance of a moving image structure image instead of changing a threshold value. The feature area detection unit 203 can easily detect the feature area from the moving image constituent image by increasing the luminance of the moving image constituent image.

  The motion vector acquisition unit 251 acquires the motion vector of the subject in the moving image. Specifically, the motion vector acquisition unit 251 acquires a motion vector included in the moving image (captured moving image data) acquired by the compressed moving image acquisition unit 201. More specifically, the motion vector acquisition unit 251 acquires a motion vector included in the MPEG moving image acquired by the compressed moving image acquisition unit 201. When the motion vector acquisition unit 251 cannot acquire a motion vector from the moving image acquired by the compressed moving image acquisition unit 201, the motion vector acquisition unit 251 includes a plurality of moving images included in the moving image expanded by the compressed moving image expansion unit 202. The motion vector of the moving image may be calculated based on the constituent image.

  The feature region prediction unit 271 should detect the feature region in the non-detected image that is another moving image constituent image based on the position of the feature region in the detected image that is the moving image constituent image from which the feature region is detected. A prediction region that is a region is specified. Specifically, the feature region prediction unit 271 specifies a prediction region in the non-detected image based on the position of the feature region in the detected image and the motion vector acquired by the motion vector acquisition unit 251.

  More specifically, the feature region predicting unit 271 calculates the position of the feature region in one or a plurality of detected images before the non-detected image in the time axis direction, and the motion vector acquired by the motion vector acquiring unit 251. Based on this, the prediction region is specified in the non-detected image. Further, the feature region prediction unit 271 is based on the position of the feature region in the detected image included in the moving image expanded by the compressed moving image expansion unit 202 and the motion vector acquired by the motion vector acquisition unit 251. The prediction area is specified in the non-detected image included in the video expanded by the above.

  Note that the feature region prediction unit 271 performs non-detection based on the position of the feature region of one or a plurality of detected images behind the non-detected image in the time axis direction and the motion vector acquired by the motion vector acquisition unit 251. The predicted region may be specified in the detected image. In addition, the feature region prediction unit 271 generates a prediction region in the non-detected image based on the position of the feature region of the detected image before and after the non-detected image in the time axis direction and the motion vector acquired by the motion vector acquisition unit 251. May be specified.

  In addition, the feature region prediction unit 271 specifies a prediction region in the non-detected image by linear interpolation based on the position of the feature region of one or a plurality of detected images preceding the non-detected image in the time axis direction. Also good. In addition, the feature region prediction unit 271 specifies a prediction region in the non-detected image by linear interpolation based on the position of the feature region in one or a plurality of detected images behind the non-detected image in the time axis direction. Also good. Further, the feature region prediction unit 271 may identify a prediction region in the non-detected image by linear interpolation based on the position of the feature region of the detected image before and after the non-detected image in the time axis direction.

  The feature region detection control unit 272 causes the feature region detection unit to detect the feature region from the prediction region of the non-detected image using a threshold value lower than the predetermined threshold value. Thereby, the feature region detection unit 203 can easily detect the feature region from the prediction region of the non-detected image. In addition, the feature region detection control unit 272 causes the feature region detection unit to detect the feature region from the prediction region of the non-detected image using a threshold value lower than the predetermined threshold, and from the region other than the prediction region of the non-detection image. The feature region detection unit is caused to detect the feature region using a predetermined threshold. Note that the feature region detection control unit 272 causes the feature region detection unit to detect the feature region from the prediction region of the non-detected image using a threshold value lower than the predetermined threshold, and from the region other than the prediction region of the non-detection image. May prevent the feature region detection unit from detecting the feature region.

  The image dividing unit 204 divides each of the plurality of moving image constituent images into a feature region and a background region. Specifically, the image dividing unit 204 divides each of the plurality of moving image constituent images into a plurality of feature regions and a background region other than the plurality of feature regions.

  The image generation unit 205 generates a feature region compression moving image for compressing the feature region moving image and a background region compression moving image for compressing the background region moving image. Specifically, the image generation unit 205 extracts a feature region image from a plurality of movie composition images included in the movie, and then generates a feature region compression movie by duplicating the extracted feature region image. . More specifically, the image generation unit 205 generates a plurality of feature region compression moving images by extracting a plurality of types of feature region images from a plurality of moving image constituent images included in the moving image. In addition, the image generation unit 205 generates a background area compression moving image by extracting a background area image from a plurality of moving image constituent images included in the moving image and then replicating the extracted background area image.

  The inclusion area specifying unit 261 specifies an inclusion area that includes a plurality of feature areas in each of the plurality of feature area compression moving images. Specifically, the inclusion area specifying unit 261 specifies, as an inclusion area, a collection area of macroblocks including a plurality of the feature areas in each of the plurality of feature area compression moving images.

  Then, the fixed value converting unit 211 converts the pixel values of regions other than the included region specified by the included region specifying unit 261 into fixed values in each of the plurality of moving image constituent images in each of the plurality of feature region compression moving images. To do. For example, the fixed value unit 211 sets the pixel value of the area other than the inclusion area to a predetermined value (for example, the luminance value 0).

  Then, the compression unit 240 compresses each of a plurality of feature region compression images including a plurality of moving image constituent images in which pixel values of regions other than the inclusion region are fixed values with an intensity corresponding to each feature amount. . In addition, the compression unit 240 encodes the inclusion region image and the region image other than the inclusion region image with different intensities for each of the plurality of feature region compression images.

  As described above, the compression unit 240 compresses each of the plurality of feature region compression moving images and the background region compression moving image with an intensity corresponding to each feature amount. The feature amount includes the type of subject, the size of the subject, the moving speed at which the moving object moves, and the size of the feature region.

  As described above, the feature region detection unit 203 detects a feature region from the image. Then, the image dividing unit 204 divides the image into a feature region and a background region other than the feature region. Then, the compression unit 240 compresses the feature area image that is the image of the feature area and the background area image that is the image of the background area with different strengths. Then, the compression unit 240 compresses the feature area moving image including a plurality of characteristic area images and the background area moving image including a plurality of background area images with different strengths.

  Note that in the compression unit 240b, the compression unit 240c, and the compression unit 240d, it is determined in advance which type of feature area moving image should be compressed, and the compression unit 240b, the compression unit 240c, and the compression unit 240d are determined in advance. The feature region moving image of the specified feature type is compressed. Note that the compression strength in the case of compressing the feature region moving image is determined in advance for each of a plurality of feature types, and the compression unit 240b, the compression unit 240c, and the compression unit 240d are features of the predetermined feature types. The area moving image is compressed with a compression strength predetermined for the type of the feature. As described above, the compression unit 240 compresses a plurality of regions in parallel using the compressor provided for each image region divided by the image dividing unit 204.

  Note that the compression unit 240 may be implemented by a single compressor, and may sequentially compress a plurality of feature area videos and background area videos. In addition, the compression unit 240 is predetermined for each feature type and background of each region for each region obtained by dividing the captured moving image decoded by the compressed moving image decompression unit 202 by the image dividing unit 204. One video data may be generated by compressing at a compression rate.

  The image quality reduction unit 221 in the compression unit 240 compresses a plurality of feature area moving images and background area moving images by reducing the image quality according to each feature amount. More specifically, the image quality reduction unit 221 compresses a plurality of feature region moving images and background region moving images by reducing the resolution or frame rate according to each feature amount.

  The encoding unit 231 in the compression unit 240 compresses a plurality of feature area moving images and background region moving images by encoding them using setting values corresponding to the respective feature amounts. For example, the encoding unit 231 compresses a plurality of feature area moving images and background area moving images by encoding them using an assigned code amount corresponding to each feature amount.

  The association processing unit 206 includes a plurality of feature region moving image data and background region moving image data generated by the compression units 240 compressing a plurality of feature region moving images and background region moving images, for example, with tag information and the like. And correspond to each other. The output unit 207 sends the plurality of feature area moving image data and background area moving image data associated by the association processing unit 206 to the communication network 110.

  FIG. 3 shows an example of a block configuration of the image processing apparatus 170. The image processing apparatus 170 includes a compressed moving image acquisition unit 301, an association analysis unit 302, a compressed moving image decompression unit 310, a composition unit 303, and an output unit 304. The compressed moving image expansion unit 310 includes a plurality of compressed moving image expansion units 311a-d (hereinafter collectively referred to as a compressed moving image expansion unit 311).

  The compressed moving image acquisition unit 301 acquires a plurality of associated feature region moving image data and background region moving image data output from the output unit 207. The association analysis unit 302 analyzes, for example, attached tag information, and extracts a plurality of associated feature region movie data and background region movie data acquired by the compressed movie acquisition unit 301.

  The compressed moving image decompression unit 311 decodes the plurality of characteristic area moving image data and background area moving image data. Specifically, the compressed moving image decompression unit 311a decodes the background area moving image data. In addition, the compressed moving image decompression unit 311b-d decodes one feature region moving image out of the plurality of feature region moving image data, and acquires a plurality of feature region moving images and a background region moving image. Note that the compressed moving image decompression unit 311b-d is provided for each type of feature, and decodes any type of feature region moving image data.

  The synthesizing unit 303 synthesizes the moving image constituent images obtained by the compressed moving image decompressing unit 311 decoding. Specifically, the synthesizing unit 303 superimposes the feature region images of the moving image constituent images included in each of the plurality of feature region moving images decoded by the compressed moving image decompression unit 311b-d on the moving image constituent images included in the background region moving image. A combined moving image composition image is generated. The output unit 304 supplies a moving image including a plurality of moving image constituent images generated by the combining unit 303 to the display device 180.

  Note that the compressed video decompression unit 310 of the present embodiment includes a plurality of compressed video decompression units 311 corresponding to the number of feature types, but in another form, one compressed video decompression unit included in the compressed video decompression unit 310. 311 may sequentially decode the background area moving image data and the plurality of characteristic area moving image data. In addition, when provided as one moving image data from the image processing device 120, one compressed moving image decompression unit 311 decodes the one moving image data, and the output unit 304 outputs the decoded moving image. May be.

  FIG. 4 shows an example of the processing flow of the image processing apparatus 120. The compressed moving image acquisition unit 201 acquires captured moving image data (401). The compressed moving image decompression unit 202 generates a plurality of frame images 410 by decoding the captured moving image data. The feature region detection unit 203 detects a region of interest (ROI) that is an example of a feature region based on the image content of the frame image 410 or the image content of the plurality of frame images 410 (402).

  The feature region detection unit 203 detects regions including human faces, human bodies, and moving objects as different types of ROIs. For example, the feature area detection unit 203 detects, by pattern matching or the like, an area including an object having a degree of coincidence with a pattern related to a predetermined person's face that is greater than a predetermined degree of coincidence, and detects the detected face area as an ROI. And Further, the feature region detection unit 203 detects a human body region including an object having a matching degree with respect to a pattern related to a human body greater than a predetermined matching degree by pattern matching or the like, and sets the detected region as an ROI. Note that the feature region detection unit 203 may detect a human body region from a region existing in the vicinity of the face region.

  In addition, the feature region detection unit 203 identifies a moving region that is a region including a moving object based on the image contents of a plurality of frame images. For example, an area in which the amount of change in pixel value with respect to another frame image is larger than a predetermined amount of change is specified as a moving area. In addition, the feature region detection unit 203 extracts objects included in each of the plurality of frame images by edge extraction or the like. Then, the feature region detection unit 203 identifies objects that are included in different positions of other frame images and that match with a degree of coincidence that is greater than a predetermined degree of coincidence, and includes an area that includes the identified object. It may be specified as a moving area.

  As described above, the feature region detection unit 203 detects a region that meets a predetermined condition relating to image content as an ROI. More specifically, the feature area detection unit 203 detects an area including an object that meets a predetermined condition as an ROI. For example, the feature area detection unit 203 detects, as an ROI, an area that includes an object having a degree of coincidence with a predetermined shape that is greater than a predetermined degree of coincidence. Further, the feature area detection unit 203 detects an area where the change amount of the image is larger than the predetermined change amount as the ROI. For example, an area where the change amount of the pixel value between other frame images is larger than a predetermined change amount is detected as the ROI.

  Then, the image processing apparatus 120 generates a moving image for compression based on the detected ROI (403). Specifically, the image dividing unit 204 divides the frame image into ROI and other areas. Then, the image generation unit 205 generates a feature region moving image 430, a feature region moving image 440, a feature region moving image 450, and a background region moving image 420 by duplicating the plurality of frame images 410. Specifically, the image generation unit 205 reproduces a plurality of frame images 410, thereby generating a facial region feature region moving image 450, a human region feature region moving image 440, a moving region feature region moving image 430, and A background area moving image 420 for the background area is generated.

  Then, the image processing apparatus 120 reduces the image quality of the feature region moving image 430, the feature region moving image 440, the feature region moving image 450, and the background region moving image 420 by the fixed value converting unit 211 and the image quality reducing unit 221. (404a, 404b, 404c, 404d). Specifically, the fixed value unit 211 changes the pixel values in the ROI divided by the image dividing unit 204 in the frame images included in each of the feature region moving image 430, the feature region moving image 440, and the feature region moving image 450. First, the pixel value for the region other than the ROI is set to a predetermined value (for example, luminance value 0). Note that the fixed value converting unit 211 may set the pixel values in the region other than the ROI as an average pixel value of the pixel values in the region near the ROI.

  As described above, the image generation unit 205 and the fixed value conversion unit 211 generate the feature region moving image 430, the feature region moving image 440, the feature region moving image 450, and the background region moving image 420 each including a plurality of frame images having the same viewing angle. The As will be described in detail later, the image processing apparatus 170 converts a moving image in which a region other than the ROI, such as the feature region moving image 430, the feature region moving image 440, and the feature region moving image 450, into a fixed value is used as the background region moving image. A moving image superimposed on 420 is generated. Therefore, the background area animation 420, the feature area animation 430, the feature area animation 440, and the feature area animation 450 can be regarded as a background layer, a motion area layer, a human area layer, and a face area layer, respectively.

  In addition, the image quality reduction unit 221 reduces the image quality of the image in the ROI in the frame images included in each of the feature region moving image 430, the feature region moving image 440, and the feature region moving image 450 according to the type of feature. Specifically, at least one of resolution, the number of gradations, and the number of colors is determined in advance as a parameter that determines the image quality of each of the face area, the human area, and the moving area. For example, a high resolution is determined in advance in the order of the face area, the human area, and the moving area.

  Then, the image quality reduction unit 221 sets the image quality of the image in the ROI in the frame image included in each of the feature region moving image 430, the feature region moving image 440, and the feature region moving image 450 to a resolution predetermined for the type of feature, Convert to an image with the number of gradations and the number of colors. In addition, the image quality reduction unit 221 makes the image quality of the frame image of the background area moving image lower than the image quality of the image in the ROI. For example, the image quality reduction unit 221 makes the resolution of the frame image of the background area moving image smaller than that of the image in the ROI.

  In addition, the image quality reduction unit 221 reduces the frame rates of the background area moving image 420, the feature area moving image 430, the feature area moving image 440, and the feature area moving image 450. For example, a frame rate is determined in advance for each type of feature, for example, for each face area, human area, and moving area. Then, the image quality reduction unit 221 thins out the frame images included in the feature region moving image 430, the feature region moving image 440, and the feature region moving image 450 at a predetermined interval according to a frame rate that is predetermined according to the type of the feature. The frame rates of the feature area animation 430, the feature area animation 440, and the feature area animation 450 are reduced. In addition, the image quality reduction unit 221 reduces the frame rate of the background area moving image 420 by thinning out the frame images included in the background area moving image 420 according to a frame rate predetermined as the frame rate of the background area moving image.

  The image quality reduction unit 221a reduces the image quality of the background area moving image 420. In addition, the image quality reduction unit 221b, the image quality reduction unit 221c, and the image quality reduction unit 221d reduce the image quality of the feature region moving image 430, the feature region moving image 440, and the feature region moving image 450, respectively.

  Then, the background area moving image encoding unit 231a and the area moving image encoding unit 231b-d encode the moving images whose image quality has been reduced by the image quality reducing unit 221 (405a, 405b, 405c, and 405d). For example, the background area moving image encoding unit 231a and the area moving image encoding unit 231b-d each encode the moving image whose image quality has been reduced by the image quality reducing unit 221.

  For example, the background area moving image encoding unit 231a performs MPEG encoding on the background area moving image with the encoding setting for the background area moving image. The feature region moving image encoding unit 231b, the feature region moving image encoding unit 231c, and the feature region moving image encoding unit 231d are encoding settings for the feature region moving image of the moving region, the human region, and the face region, respectively. Each area moving image is MPEG-encoded. Note that the coding setting includes setting a quantization table in MPEG coding, for example. The encoding setting will be described with reference to FIG.

  Then, the association processing unit 206 adds tag information to the background region moving image data and the plurality of feature region moving image data obtained by encoding by the background region moving image encoding unit 231a and the feature region moving image encoding unit 231b-d. The output unit 207 outputs the information to the display device 180 by associating it with an accessory (406). At this time, the association processing unit 206 adds timing information (for example, time stamp) including information indicating the display timing of the frame image included in each of the background area moving image and the plurality of characteristic area moving images to the tag information or the like. Good. In addition, the association processing unit 206 identifies the imaging device 100 that captured the feature region information including information indicating the ranges of the plurality of feature regions, the background region movie, and the captured movie data that is the basis of the plurality of feature region movies. Identification information or the like to be added may be added to tag information or the like.

  As described above, the feature region detection unit 203 detects a plurality of feature regions having different types of subjects from a plurality of moving image constituent images included in a moving image that is an image. Then, the compression unit 240 compresses the plurality of feature area moving images with an intensity corresponding to the type of each subject. In the present embodiment, a human face and a human body region have been described as examples of the types of subjects. However, in other examples, vehicle license plates and vehicle bodies other than license plates may be used as the types of subjects.

  Further, the front face and the side face of the person may be the subject type. Further, a stationary subject and a moving subject may be used as the subject type. Further, the feature region detection unit 203 may detect a region including a plurality of subjects having different distances from the imaging device 100 to the subject as a plurality of feature regions having different types of features.

  Note that the compression unit 240 may compress the motion region, the human body, the side profile of the person, and the face in front of the person with high compression strength, which are examples of feature types. In the present embodiment, in consideration of the purpose of using the image processing system 10 as a monitoring system, an area including a human face is detected as an ROI, and the detected ROI has a higher image quality than an area other than the ROI. . However, the image processing system 10 can also be used as, for example, a system that captures landscapes of street corners. When the image processing system 10 is used in such a form, for the purpose of protecting personal information, an area including a human face is detected as an ROI, and the detected ROI has a lower image quality than an area other than the ROI. It may be. For example, the compressing unit 240 may compress the feature region moving image and the background region moving image with a large compression strength in the order of the face in front of the person, the profile of the person, the human body, the motion region, and the background region.

  In addition, the feature region detection unit 203 may detect a plurality of feature regions having different subject velocities from a plurality of frame images. In this case, the image quality reduction unit 221 may convert the feature area moving image into a moving image having a higher frame rate as the subject speed increases. As described above, the compression unit 240 may compress a plurality of feature region moving images with an intensity corresponding to the speed of each subject.

  As described above, the image processing apparatus 120 generates a plurality of feature region moving images and background region moving images having the same viewing angle by fixing a region other than the ROI in the frame image included in the feature region moving image. For this reason, according to the image processing apparatus 120, the feature region moving image may be compressed at a high compression rate using a general-purpose encoder without using a specially designed encoder. For example, when a feature area moving image is encoded using a motion vector as in MPEG encoding, the difference value between pixel values is often 0 for a macroblock in a fixed value area. Therefore, such fixed values may reduce the manufacturing cost of the image processing apparatus 120 while maintaining a high compression rate.

  In the above description, the compression unit 240 compresses the feature region moving image including the frame image in which the region other than the ROI region is fixed. Note that the compression unit 240 may cut out and compress an image in the ROI in the frame image included in the feature area moving image and output it as a feature area moving image.

  When the feature area detection unit 203 has not detected the ROI, the output unit 207 outputs the background area moving image data output from the compression unit 240a to the image processing apparatus 170. In this case, the image generation unit 205 does not have to generate the feature region moving image 430, the feature region moving image 440, and the feature region moving image 450. Then, the image generation unit 205 generates the feature region moving image 430, the feature region moving image 440, and the feature region moving image 450 on condition that the feature region detection unit 203 detects the ROI, and the output unit 207 performs the above processing. The plurality of characteristic area moving image data and background area moving image data generated by the above is output to the image processing apparatus 170. During this time, the compression unit 240a may continue to compress the background area moving image 420 at a predetermined compression ratio for the background area in order to compress the background area moving image 420.

  In addition, while the feature region detection unit 203 does not detect the ROI, the compression unit 240 is set in advance to be lower than the compression rate for the background region and higher than the compression rate for compressing the feature region moving image. The background area moving image may be compressed at the ROI non-detection period compression rate. Then, the compression unit 240 may compress the background region moving image with the background region compression rate on condition that the feature region detection unit 203 detects the ROI. At this time, the compression unit 240 may compress the feature region moving image at a compression rate lower than the ROI non-detection period compression rate.

  The compression unit 240 compresses the background region moving image of a predetermined period after the ROI is detected by the feature region detection unit 203 at the ROI non-detection period compression rate, and a period longer than the predetermined period elapses. As a condition, the background area moving image may be compressed at the compression ratio for the background area. In this case, even when the region that should originally be detected as ROI is not detected as ROI, a background region moving image having a certain level of image quality may be provided. The compression unit 240 also sets the image quality of the region including the ROI region in the other frame image estimated from the position of the ROI region in the plurality of frame images detected by the feature region detection unit 203 to be higher than the image quality of the other region. Therefore, the compression rate may be different for each region.

  FIG. 5 shows an example of the image quality of a plurality of feature area videos and background area videos. Here, for the purpose of simplifying the description, it is assumed that the frame rate of the captured moving image data acquired by the compressed moving image acquisition unit 201 is 16 fps, and the resolution of the frame image included in the captured moving image data is 72 dpi.

  The resolution ratio indicating the ratio of the resolution of the frame image included in the background area moving image 420 after image quality reduction to the resolution of the frame image 410 included in the captured moving image is predetermined as 1/8. The image quality reduction unit 221 generates a 9 dpi frame image having a resolution of 1/8 with respect to the frame image included in the background area video 420 before image quality reduction generated by copying the captured video by the image generation unit 205. This is generated by thinning out the pixels of the frame image included in the background area moving image 420 before image quality reduction. In addition, the frame rate ratio indicating the ratio of the frame rate of the background area moving image 420 after image quality reduction to the frame rate of the captured moving image is set to 1/8 in advance. The image quality reduction unit 221 converts the background area video 420 having a frame rate of 2 fps, which is a frame rate of 1/8 of the frame rate of the background area video 420 before the image quality reduction, into a frame image included in the background area video 420 before the image quality reduction. Generate by thinning out.

  Similarly, a resolution ratio and a frame rate ratio are determined for each of the plurality of characteristic area moving images. For example, the resolution ratio and the frame rate ratio are set to 1/4 for the feature area moving image 430, and the resolution ratio and the frame rate ratio are set to 1/2 for the feature area moving image 440. Is defined as 1/1 as the resolution ratio and the frame rate ratio. As a result, the image quality reduction unit 221b generates a feature region moving image 430 having a frame rate of 4 fps and a frame image resolution of 18 dpi. In addition, the image quality reduction unit 221c generates a feature region moving image 440 having a frame rate of 8 fps and a frame image resolution of 36 dpi. In addition, the image quality reduction unit 221d generates a feature region moving image 450 having a frame rate of 16 fps and a frame image resolution of 72 dpi.

  In the above example, the case where the image quality reduction unit 221 reduces the image quality of the frame image by thinning out the pixels of the frame image included in the plurality of feature region moving images and the background region moving image has been described as an example. In addition, the image quality reduction unit 221 may reduce the image quality of the frame image using a filter that passes through a predetermined frequency region, such as a low-pass filter. In this case, the frequency band through which the filter passes and the intensity indicating the degree of passage may be determined in advance for each type of feature, for example, for each of the background region, the moving region, the human region, and the face region.

  In addition to the image quality reduction by the image quality reduction unit 221, or in place of the image quality reduction by the image quality reduction unit 221, the encoding unit 231 may reduce the image quality of the frame image. For example, the encoding unit 231 can reduce the image quality by increasing the value of the quantization table in MPEG encoding. The magnitude of the value of the quantization table may be determined in advance for each type of feature. For example, each of the background region moving image encoding unit 231a and the plurality of feature region moving image encoding units 231b-d may perform encoding using a quantization table having a preset value. In addition, a value for each frequency component in the quantization table may be determined in advance for each type of feature.

  Further, the image quality reduction unit 221 may further average a plurality of frame images included in the background area moving image. According to this, when an object indicating a moving object is included in the frame image, a frame image in which the objects of the moving object are averaged is obtained. When such a plurality of frame images are continuously displayed, the movement of the moving object may appear smoothly in the viewer's eyes.

  In the above description, after the image generation unit 205 replicates the captured moving image, frame images included in a plurality of feature region moving images and background region moving images obtained by copying are thinned out or pixels are thinned out. In the above, the mode of compressing a plurality of feature region moving images and background region moving images has been described. In addition, the image generation unit 205 generates a plurality of feature area videos and background area videos with a reduced frame rate by thinning out and selecting a plurality of frame images included in the captured video according to the frame rate ratio. Also good. Then, the image quality of the plurality of feature area moving images and the background area moving images may be reduced by the fixed value converting unit 211a fixing the value and the image quality reducing unit 221 reducing the resolution.

  FIG. 6 shows an example of the processing flow of the image processing apparatus 170. The compressed moving image acquisition unit 301 acquires a plurality of associated feature area moving image data and background area moving image data from the image processing device 120, and identifies timing information, information for identifying the imaging device 100, and the like using the attached tag information. Is acquired (601). Then, the compressed moving image decompression unit 311 generates a background region moving image 610 indicating a background layer by decoding a plurality of feature region moving image data and background region moving image data, respectively. (602a) At the same time, the compressed video decompression unit 311 generates a feature area video 620 indicating a moving area layer, a feature area video 630 indicating a human area layer, and a feature area video 640 indicating a face area layer (602b, 602c, And 602d).

  The synthesizing unit 303 synthesizes frame images included in the background area moving image 610, the characteristic area moving image 620, the characteristic area moving image 630, and the characteristic area moving image 640 (603). At this time, the synthesis unit 303 enlarges the frame image so that the subject at the same position as the frame image having the maximum resolution overlaps according to the resolution of the frame image included in each of the background area moving image and the plurality of characteristic area moving images. Then, the enlarged frame images are superimposed to generate a composite frame image.

  At this time, the synthesizing unit 303 cuts out the feature region image in the frame image included in the feature region moving image 620, the feature region moving image 630, and the feature region moving image 640, and overwrites the frame image included in the background region moving image 610. To generate a composite frame image. In addition, when the frame rates of the background area moving image 610, the feature area moving image 620, the feature area moving image 630, and the feature area moving image 640 are different, the synthesizing unit 303 performs the background area moving image 610, the feature area moving image 620, and the feature area moving image 630. , And the latest frame image of the feature region moving image 640 are synthesized.

  Thereby, the composition unit 303 generates a composite frame image. The combining unit 303 generates a combined moving image 650 including a plurality of combined frame images. Then, the output unit 304 selects the display device 180 that displays the composite video based on the tag information acquired by the compressed video acquisition unit 301 and supplies the composite video to the selected display device 180 (604).

  FIG. 7 shows an example of a method for specifying a feature region in a plurality of moving image constituent images. In FIG. 7, a moving image 700 shown in the upper part shows a moving image in a state where the prediction region in the non-detected image is specified by the feature region prediction unit 271. On the other hand, the moving image 700 shown in the lower row shows a moving image in a state where the feature region in the non-detected image is detected by the feature region detection unit 203. The moving image 700 includes continuous moving image constituent images 701 to 705.

  Of the moving image constituent images included in the moving image 700, the moving image constituent image 701 and the moving image constituent image 702 indicate detection images in which the feature region is detected by the feature region detection unit 203 using a predetermined threshold. Of the moving image constituent images included in the moving image 700, the moving image constituent image 703, the moving image constituent image 704, and the moving image constituent image 705 were not detected by the feature region detection unit 203 using a predetermined threshold. A detection image is shown.

  As shown in the upper part of FIG. 7, the feature region detection unit 203 detects the feature region 701a from the moving image composition image 701 and detects the feature region 702a from the movie composition image 702 using a predetermined threshold. On the other hand, the feature region detection unit 203 does not detect a feature region from the moving image composition image 703, the moving image composition image 704, and the moving image composition image 705 using a predetermined threshold. Instead, the feature region prediction unit 271 specifies the prediction region 703a in the moving image composition image 703. Also, the feature region prediction unit 271 specifies the prediction region 704a in the moving image composition image 704. Then, the feature region prediction unit 271 specifies the prediction region 705a in the moving image composition image 705.

  Thereafter, the feature region detection unit 203 controlled by the feature region detection control unit 272 detects the feature region 703b from the prediction region 703a in the moving image composition image 703 using a threshold value lower than a predetermined threshold value. Similarly, the feature region detection unit 203 detects the feature region 704b from the prediction region 704a in the moving image composition image 704 using a threshold value lower than the predetermined threshold value. Similarly, the feature region detection unit 203 detects the feature region 705b from the prediction region 705a in the moving image composition image 705 using a threshold value lower than the predetermined threshold value. As a result, the feature region detection unit 203 identifies the feature region in each of the moving image constituent images 701 to 705 as shown in the lower part of FIG.

  The feature region prediction unit 271 specifies the prediction region 703a, the prediction region 704a, and the prediction region 705a using the motion vector of the moving image 700 based on the position of the feature region 701a and the position of the feature region 702a. Note that the feature region prediction unit 271 may specify the prediction region 703a, the prediction region 704a, and the prediction region 705a by linear interpolation based on the position of the feature region 701a and the position of the feature region 702a.

  As described above, in the image processing apparatus 120 according to the present embodiment, the feature region detection unit 203 detects a feature region using a predetermined threshold for a detected image. On the other hand, for the non-detected image, the image processing apparatus 120 according to the present embodiment uses the threshold lower than the predetermined threshold by the feature area detection unit 203 after the feature area prediction unit 271 specifies the prediction area. A feature region is detected from the prediction region. As a result, when the image processing apparatus 120 of the present embodiment is applied to an actual monitoring system, it is easy to detect a feature region from a prediction region in a non-detected image. In some cases, the accuracy of detection can be improved. In addition, since it is possible to narrow down the target area of the feature area in the non-detected image, the processing time when the feature area detection unit 203 detects the feature area may be shortened.

  FIG. 8 shows an example of a method for fixing areas other than the inclusion area. In FIG. 8, a moving image 800 indicates a moving image in which an inclusion region is specified by the inclusion region specifying unit 261 and a region other than the inclusion region is fixed by the fixed value conversion unit 211. The moving image 800 includes continuous moving image constituent images 801-805.

  In each of the moving image composition images 801 to 805, the inclusion area 810 indicates an area that includes each feature area of the moving image composition images 801 to 805 specified by the inclusion area specifying unit 261. Of the feature regions of the moving image composition images 801 to 805, the feature region of the moving image composition image 801 and the feature region of the moving image composition image 802 are detected by the feature region detection unit 203 using a predetermined threshold. In addition, the feature region detection unit 203 uses a threshold value lower than a predetermined threshold value by the feature region detection unit 203 for the feature region of the movie composition image 803, the feature region of the movie composition image 804, and the feature region of the movie composition image 805. Has been detected.

  Further, in each of the moving image constituent images 801 to 805, the pixel value of the region other than the inclusion region 810 is fixed to “0” by the fixed value converting unit 211. As described above, the image processing apparatus 120 according to the present embodiment specifies an inclusion region that includes the feature regions of a plurality of moving image constituent images, and then fixes a region other than the inclusion region to a fixed value. As a result, when the image processing apparatus 120 of the present embodiment is applied to an actual monitoring system, it is possible to reduce the amount of difference in pixel values in regions other than the inclusion region between moving image constituent images. In some cases, the compression rate of difference data between moving image constituent images can be increased.

  FIG. 9 shows an example of the hardware configuration of the image processing device 120 and the image processing device 170. The image processing device 120 and the image processing device 170 include a CPU peripheral unit, an input / output unit, and a legacy input / output unit. The CPU peripheral section includes a CPU 1505, a RAM 1520, a graphic controller 1575, and a display device 1580 that are connected to each other by a host controller 1582. The input / output unit includes a communication interface 1530, a hard disk drive 1540, and a CD-ROM drive 1560 that are connected to the host controller 1582 by the input / output controller 1584. The legacy input / output unit includes a ROM 1510, a flexible disk drive 1550, and an input / output chip 1570 connected to the input / output controller 1584.

  The host controller 1582 connects the RAM 1520, the CPU 1505 that accesses the RAM 1520 at a high transfer rate, and the graphic controller 1575. The CPU 1505 operates based on programs stored in the ROM 1510 and the RAM 1520 to control each unit. The graphic controller 1575 acquires image data generated by the CPU 1505 or the like on a frame buffer provided in the RAM 1520 and displays the image data on the display device 1580. Alternatively, the graphic controller 1575 may include a frame buffer that stores image data generated by the CPU 1505 or the like.

  The input / output controller 1584 connects the host controller 1582 to the hard disk drive 1540, the communication interface 1530, and the CD-ROM drive 1560, which are relatively high-speed input / output devices. The hard disk drive 1540 stores programs and data used by the CPU 1505. The communication interface 1530 is connected to the network communication device 1598 to transmit / receive programs or data. The CD-ROM drive 1560 reads a program or data from the CD-ROM 1595 and provides it to the hard disk drive 1540 and the communication interface 1530 via the RAM 1520.

  The input / output controller 1584 is connected to the ROM 1510, the flexible disk drive 1550, and the relatively low-speed input / output device of the input / output chip 1570. The ROM 1510 stores a boot program that is executed when the radiation imaging system is started up, a program that depends on the hardware of the radiation imaging system, and the like. The flexible disk drive 1550 reads a program or data from the flexible disk 1590 and provides it to the hard disk drive 1540 and the communication interface 1530 via the RAM 1520. The input / output chip 1570 connects various input / output devices via the flexible disk drive 1550 or a parallel port, serial port, keyboard port, mouse port, and the like.

  A program executed by the CPU 1505 is stored in a recording medium such as the flexible disk 1590, the CD-ROM 1595, or an IC card and provided by the user. The program stored in the recording medium may be compressed or uncompressed. The program is installed in the hard disk drive 1540 from the recording medium, read into the RAM 1520, and executed by the CPU 1505.

  The program executed by the CPU 1505 includes the image processing device 120, the compressed moving image acquisition unit 201, the compressed moving image decompression unit 202, the feature region detection unit 203, the image division unit 204, and the image described with reference to FIGS. It functions as the generation unit 205. Further, the program executed by the CPU 1505 causes the image processing apparatus 120 to be connected to the fixed value conversion unit 211, the image quality reduction unit 221, the encoding unit 231, the association processing unit 206 described with reference to FIGS. It functions as the output unit 207.

  Further, the program executed by the CPU 1505 causes the image processing apparatus 120 to execute the motion vector acquisition unit 251, the feature region prediction unit 271, the feature region detection control unit 272, and the inclusion region specification described with reference to FIGS. 1 to 9. The unit 261 functions. Further, the program executed by the CPU 1505 causes the image processing apparatus 170 to be connected to the compressed moving image acquisition unit 301, the association analysis unit 302, the compressed moving image decompression unit 311, the combining unit 303, which are described with reference to FIGS. It functions as the output unit 304.

  The program shown above may be stored in an external storage medium. As the storage medium, in addition to the flexible disk 1590 and the CD-ROM 1595, an optical recording medium such as a DVD or PD, a magneto-optical recording medium such as an MD, a tape medium, a semiconductor memory such as an IC card, or the like can be used. Further, a storage device such as a hard disk or a RAM provided in a server system connected to a dedicated communication network or the Internet is used as a recording medium, and is provided to the image processing device 120 and the image processing device 170 as a program via the network. Also good.

  As mentioned above, although this invention was demonstrated using embodiment, the technical scope of this invention is not limited to the range as described in the said embodiment. It will be apparent to those skilled in the art that various modifications or improvements can be added to the above-described embodiment. It is apparent from the scope of the claims that the embodiments added with such changes or improvements can be included in the technical scope of the present invention.

1 shows an example of an image processing system 10 according to an embodiment. 2 shows an example of a block configuration of an image processing apparatus 120. 2 shows an example of a block configuration of an image processing apparatus 170. An example of the processing flow of the image processing apparatus 120 is shown. An example of the image quality of a plurality of feature area videos and background area videos is shown. An example of the processing flow of the image processing apparatus 170 is shown. An example of a method for specifying a feature region in a plurality of moving image constituent images will be described. An example of a method for fixing a region other than an inclusion region to a fixed value is shown. An example of the hardware configuration of the image processing apparatus 120 and the image processing apparatus 170 is shown.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Image processing system 100 Imaging device 110 Communication network 120 Image processing device 130 Person 140 Moving object 150 Monitoring object space 160 Space 170 Image processing device 180 Display device 201 Compressed moving image acquisition unit 202 Compressed moving image decompression unit 203 Feature area detection unit 204 Image division Unit 205 image generation unit 206 association processing unit 207 output unit 210 fixed value unit 211 fixed value unit 220 reduction unit 221 image quality reduction unit 230 encoding unit 231 encoding unit 231a background area moving image encoding unit 231b-d Features Region moving image encoding unit 240 compression unit 251 motion vector acquisition unit 271 feature region prediction unit 272 feature region detection control unit 260 inclusion region specification unit 261 inclusion region specification unit 301 compressed movie acquisition unit 302 association analysis unit 310 compression movie expansion unit 3 11 Compressed video decompression unit 303 Compositing unit 304 Output unit

Claims (11)

A feature region detection unit that detects a feature region from a movie constituent image included in the movie using a predetermined threshold;
Based on the position of the feature region in the detected image that is the moving image constituent image from which the feature region has been detected, the feature region should be detected in the non-detected image that is the moving image constituent image other than the detected image A feature region prediction unit that identifies a prediction region,
An image processing apparatus comprising: a feature region detection control unit that causes the feature region detection unit to detect the feature region from the prediction region of the non-detected image using a threshold value lower than the predetermined threshold value. The feature region detection control unit
From the predicted region of the non-detected image, using the threshold lower than the predetermined threshold, the feature region detection unit is detected,
The image processing apparatus according to claim 1, wherein the feature region detection unit is detected from the region other than the prediction region of the non-detected image by using the predetermined threshold.   The image according to claim 1, wherein the feature region prediction unit identifies the prediction region in the non-detected image based on a position of the feature region in each of the plurality of detected images preceding the non-detected image. Processing equipment.   The feature region predicting unit is configured to detect the prediction region in the non-detected image based on the position of the feature region in each of the detected image before the non-detected image and the detected image after the non-detected image. The image processing apparatus according to claim 1, wherein the image processing apparatus is specified. A motion vector acquisition unit that acquires a motion vector of a subject in the video;
The image processing device according to claim 1, wherein the feature region prediction unit identifies the prediction region in the non-detected image based on the position of the feature region in the detected image and the motion vector. A compressed video acquisition unit that acquires a compressed video including the motion vector;
A compressed video expansion unit that expands the video acquired by the compressed video acquisition unit,
The feature region detection unit detects the feature region using the predetermined threshold value from the moving image constituent image included in the moving image expanded by the compressed moving image expansion unit,
The motion vector acquisition unit acquires the motion vector included in the video acquired by the compressed video acquisition unit;
The feature region prediction unit identifies the prediction region in the non-detected image included in the moving image expanded by the compressed moving image expansion unit based on the position of the feature region in the detected image and the motion vector. Item 8. The image processing apparatus according to Item 1. The compressed video acquisition unit acquires an MPEG video including the motion vector,
The compressed video decompression unit decompresses the MPEG video acquired by the compressed video acquisition unit,
The feature region detection unit detects the feature region using the predetermined threshold value from the moving image constituent image included in the MPEG moving image expanded by the compressed moving image expansion unit,
The image processing apparatus according to claim 6, wherein the motion vector acquisition unit acquires the motion vector included in the MPEG video acquired by the compressed video acquisition unit. An image dividing unit that divides each of the detected image and the non-detected image into the feature region and a background region other than the feature region;
The image processing apparatus according to claim 1, further comprising: an encoding unit that encodes the image of the feature region and the image of the background region with different intensities. An inclusion area specifying unit for specifying an inclusion area including the feature area specified in the detection image and the non-detection image;
A fixed value unit for fixing a pixel value of a region other than the inclusion region in each of the detected image and the non-detected image;
The image processing apparatus according to claim 8, wherein the encoding unit compresses the image of the inclusion region and the image of the region other than the inclusion region with different intensities. A feature region detection stage for detecting a feature region using a predetermined threshold value from a movie constituent image included in the movie;
Based on the position of the feature region in the detected image that is the moving image constituent image from which the feature region has been detected, the feature region should be detected in the non-detected image that is the moving image constituent image other than the detected image A feature region prediction stage that identifies a prediction region that is
An image processing method comprising: a feature region detection control step of causing the feature region detection step to detect the feature region using a threshold value lower than the predetermined threshold value from the prediction region of the non-detected image. A program for an image processing apparatus for encoding an image, wherein the image processing apparatus is
A feature region detection unit that detects a feature region from a moving image constituent image included in the moving image using a predetermined threshold;
Based on the position of the feature region in the detected image that is the moving image constituent image from which the feature region has been detected, the feature region should be detected in the non-detected image that is the moving image constituent image other than the detected image A feature region prediction unit that identifies a prediction region,
A program that causes the feature region detection unit to function as a feature region detection control unit that detects the feature region from the prediction region of the non-detected image using a threshold value that is lower than the predetermined threshold value.

Images