Abstract: An image processing apparatus has: a segmenting unit for segmenting an input image into a plurality of areas on the basis of a similarity of pixels; an acquiring unit for acquiring sizes of the segmented areas; a selecting unit for selecting one of a plurality of discriminating methods of discriminating, with respect to adjacent areas among the plurality of areas, on the basis of an acquired size of each of the adjacent areas, whether or not the adjacent areas are connecting targets by using different kinds of features; an extracting unit for extracting, from the adjacent areas, the feature of the kind which is used in the selected discriminating method; a connecting unit for connecting the adjacent areas determined as the connecting targets by the selected discriminating method; and a classifying unit for classifying a kind of connected area.

Abstract: An image processing apparatus includes an object detection unit configured to detect a position of an object based on an input image, and a segmentation unit configured to segment, according to a result of detection by the object detection unit, the image into a plurality of regions, each of which includes adjacent similar pixels and has a size determined for each position in the image.

Abstract: An image recognizing apparatus is equipped with: a detecting unit configured to detect, from an input image, a candidate area for a target of recognition, based on a likelihood of a partial area in the input image; an extracting unit configured to extract, from a plurality of candidate areas detected by the detecting unit, a set of the candidate areas which are in an overlapping relation; a classifying unit configured to classify an overlapping state of the set of the candidate areas; and a discriminating unit configured to discriminate whether or not the respective candidate areas are the target of recognition, based on the overlapping state of the set of the candidate areas and the respective likelihoods of the candidate areas.

Abstract: A recognition apparatus includes a calculation unit configured to calculate likelihood of each feature quantity based on the weighted distribution of the feature quantity extracted from a plurality of learning images, a correction unit configured, if a ratio of a learning image to a specific feature quantity is equal to or smaller than a predetermined ratio and a weight for the specific feature quantity is greater than a predetermined value, to correct the value of likelihood of the specific feature quantity to lower the value based on the distribution, a setting unit configured to set the likelihood corrected by the correction unit in association with a feature quantity, and a discrimination unit to extract a feature quantity from an input image and discriminate whether the input image includes a predetermined object based on the likelihood associated with the feature quantity.

Abstract: An image processing apparatus has: a segmenting unit for segmenting an input image into a plurality of areas on the basis of a similarity of pixels; an acquiring unit for acquiring sizes of the segmented areas; a selecting unit for selecting one of a plurality of discriminating methods, with respect to adjacent areas among the plurality of areas, on the basis of an acquired size of each of the adjacent areas, whether or not the adjacent areas are connecting targets by using different kinds of features; an extracting unit for extracting, from the adjacent areas, the feature of the kind which is used in the selected discriminating method; a connecting unit for connecting the adjacent areas determined as the connecting targets by the selected discriminating method; and a classifying unit for classifying a kind of connected area.

Abstract: An image processing apparatus acquires a plurality of input images which are serially photographed, detects a plurality of object regions from each input image, and associates object regions in a past input image with object regions in a current input image. If any object region that has not been appropriately associated exists in the object regions detected from the past input image, the apparatus calculates object region movement information for each size of the object region based on the object regions mutually associated between the past input image and the current input image, and estimates a position of the object region of the current input image that has not been associated based on the movement information for each size of the object region and a size of the object region that has not been associated.

Abstract: An image processing apparatus includes an object detection unit configured to detect a position of an object based on an input image, and a segmentation unit configured to segment, according to a result of detection by the object detection unit, the image into a plurality of regions, each of which includes adjacent similar pixels and has a size determined for each position in the image.

Abstract: An image recognition apparatus includes: a storage unit configured to store a dictionary used to recognize a predetermined pattern; a recognition unit configured to detect in image data using the dictionary, as recognition results, a plurality of partial regions having a likelihood of being the predetermined pattern greater than a predetermined threshold; a display unit configured to display the image data, and also display information indicating the partial regions that were detected by the recognition unit; a determination unit configured to determine, based on an instruction by a user, a negative region from among the plurality of partial regions that were detected by the recognition unit; a generation unit configured to generate a learning image based on the determined negative region; and an update unit configured to update the dictionary based on the learning image that was generated by the generation unit.

Abstract: An image recognizing apparatus is equipped with: a detecting unit configured to detect, from an input image, a candidate area for a target of recognition, based on a likelihood of a partial area in the input image; an extracting unit configured to extract, from a plurality of candidate areas detected by the detecting unit, a set of the candidate areas which are in an overlapping relation; a classifying unit configured to classify an overlapping state of the set of the candidate areas; and a discriminating unit configured to discriminate whether or not the respective candidate areas are the target of recognition, based on the overlapping state of the set of the candidate areas and the respective likelihoods of the candidate areas.

Abstract: For each pixel of interest in a local region of an input image, an edge intensity in each of a plurality of predetermined directions is calculated. All directions in which the edge intensities are larger than an average value of the edge intensities are selected. For all pixels of interest in the local region, the edge intensities calculated for each of the selected directions are accumulated and output as an edge feature amount.

Abstract: A recognition apparatus includes a calculation unit configured to calculate likelihood of each feature quantity based on the weighted distribution of the feature quantity extracted from a plurality of learning images, a correction unit configured, if a ratio of a learning image to a specific feature quantity is equal to or smaller than a predetermined ratio and a weight for the specific feature quantity is greater than a predetermined value, to correct the value of likelihood of the specific feature quantity to lower the value based on the distribution, a setting unit configured to set the likelihood corrected by the correction unit in association with a feature quantity, and a discrimination unit to extract a feature quantity from an input image and discriminate whether the input image includes a predetermined object based on the likelihood associated with the feature quantity.

Abstract: An image processing apparatus, includes an input unit that inputs a plurality of input images. The image processing apparatus also includes an acquisition unit that acquires photographic information added to each of the plurality of input images. The image processing apparatus further includes a first setting unit that sets control information used to control a layout of each of the plurality of input images in accordance with whether or not the photographic information indicates that the respective input image is photographed with emphasis on an object. The image processing apparatus further includes a generator that generates an output image on which each of the plurality of input images is configured to have an image size according to the control information of the respective input image.

Abstract: An image processing apparatus acquires a plurality of input images which are serially photographed, detects a plurality of object regions from each input image, and associates object regions in a past input image with object regions in a current input image. If any object region that has not been appropriately associated exists in the object regions detected from the past input image, the apparatus calculates object region movement information for each size of the object region based on the object regions mutually associated between the past input image and the current input image, and estimates a position of the object region of the current input image that has not been associated based on the movement information for each size of the object region and a size of the object region that has not been associated.

Abstract: The color of a tooth image region is corrected so as not to form an unnatural face image. To this end, a first image region corresponding to teeth is detected from the image. A second image region corresponding to a face portion other than the teeth is detected from the image. Then, the color of the first image region is corrected based on the feature amounts of the colors of the first and second image regions.

Abstract: An image recognition apparatus includes: a storage unit configured to store a dictionary used to recognize a predetermined pattern; a recognition unit configured to detect in image data using the dictionary, as recognition results, a plurality of partial regions having a likelihood of being the predetermined pattern greater than a predetermined threshold; a display unit configured to display the image data, and also display information indicating the partial regions that were detected by the recognition unit; a determination unit configured to determine, based on an instruction by a user, a negative region from among the plurality of partial regions that were detected by the recognition unit; a generation unit configured to generate a learning image based on the determined negative region; and an update unit configured to update the dictionary based on the learning image that was generated by the generation unit.

Abstract: For each pixel of interest in a local region of an input image, an edge intensity in each of a plurality of predetermined directions is calculated. All directions in which the edge intensities are larger than an average value of the edge intensities are selected. For all pixels of interest in the local region, the edge intensities calculated for each of the selected directions are accumulated and output as an edge feature amount.

Abstract: An image processing apparatus segments a determination target image into regions, reads an image type determination condition that includes a plurality of object determination conditions concerning an object related to the region of the image from a storage device, and calculates a feature quantity of the segmented region. The image processing apparatus determines whether the segmented region satisfies at least one object determination condition that is included in the image type determination condition based on the plurality of object determination conditions included in the read image type determination condition and the calculated feature quantity of the region, and identifies an image type of the determination target image based on the region concerning the determination target image that is determined as satisfying the object determination condition.

Abstract: A method of controlling an image processing apparatus, the method includes inputting a plurality of images; acquiring additional information added to each of the plurality of images; setting control information used to control a layout of the plurality of images in accordance with the additional information; and generating an output image on which each of the plurality of images is configured to have an image size according to the control information of the respective image.

Abstract: The color of a tooth image region is corrected so as not to form an unnatural face image. To this end, a first image region corresponding to teeth is detected from the image. A second image region corresponding to a face portion other than the teeth is detected from the image. Then, the color of the first image region is corrected based on the feature amounts of the colors of the first and second image regions.