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 comprises: an image acquiring unit to acquire an image including an object; a dividing unit to divide the image, which is acquired by the image acquiring unit, into a plurality of superpixels based on similarity of adjacent pixels; a candidate area acquiring unit to acquire, from the superpixels divided by the dividing unit, a plurality of candidate areas acting as candidates of an area of the object; an extracting unit to extract a feature quantity from each of the plurality of candidate areas acquired by the candidate area acquiring unit; a checking unit to check the feature quantity, which is extracted from each candidate area by the extracting unit, against registered information concerning a feature quantity of object area; and an outputting unit to output the area of the object in the image, based on a checked result by the checking unit.

Abstract: An image is obtained. At least one local region is set in the image. Feature patterns are extracted from the local region, and, out of a plurality of bins corresponding to a plurality of patterns which can form the feature patterns, bins that have been determined in accordance with a type of the local region are set as histogram bins used in generating a histogram. A histogram is generated corresponding to the extracted feature patterns using the set histogram bins, and image recognition is performed using the generated histogram.

Abstract: There is provided a semiconductor device including an ohmic junction layer which is excellent in surface flatness and uniformity of composition in an interface with a semiconductor substrate and thus can give a sufficiently high adhesiveness with a Schottky junction layer.

Abstract: An object recognition apparatus comprises: an extraction unit configured to extract a partial region from an image and extract a feature amount; a recognition unit configured to recognize whether the partial region is a target object based on the feature amount and one of a first recognition model including a feature amount of a positive example indicating the target object and a negative example indicating a background and a second recognition model including that of the positive example; an updating unit configured to update the first recognition model by adding the feature amount; and an output unit configured to output an object region recognized as being the target object, wherein the recognition unit performs recognition based on the first recognition model if the object region was output for a previous image, and based on the second recognition model if not.

Abstract: A dictionary data registration apparatus includes a dictionary configured to be registered a local feature amount for each region of an image with respect to each of a plurality of categories, an extraction unit configured to extract the local feature amount from a plurality of regions of an input image, a selection unit configured to select a plurality of the local feature amounts for each region according to a distribution of the local feature amounts extracted by the extraction unit from a plurality of regions of a plurality of pieces of input images which belongs to the category with respect to each of the plurality of categories, and a registration unit configured to register the selected plurality of local feature amounts on the dictionary as a local feature amount for each region with respect to the category.

Abstract: In an object detection system with a first and a second image processing apparatus, the first image processing apparatus includes a reduction unit configured to reduce an input image, a first detection unit configured to detect a predetermined object from a reduction image reduced by the reduction unit, and a transmission unit configured to transmit the input image and a first detection result detected by the first detection unit to the second image processing apparatus, and the second image processing apparatus includes a reception unit configured to receive the input image and the first detection result from the first image processing apparatus, a second detection unit configured to detect the predetermined object from the input image, and an output unit configured to output the first detection result and a second detection result detected by the second detection unit.

Abstract: In a pattern recognition apparatus, a characteristic amount calculation unit calculates a characteristic amount for recognizing a desired object from a partial image clipped from an input pattern, a likelihood calculation unit calculates a likelihood of an object as a recognition target from the characteristic amount calculated by the characteristic amount calculation unit by referring to an object dictionary, and an object determination unit determines whether the partial image is the object as the recognition target based on the likelihood of the object calculated by the likelihood calculation unit. The likelihood calculation unit calculates the likelihood of the object as the recognition target from the characteristic amount calculated by the characteristic amount calculation unit by referring to a specific object dictionary.

Abstract: An image recognition apparatus comprising: an obtaining unit configured to obtain one or more images; a detection unit configured to detect a target object image from each of one or more images; a cutting unit configured to cut out one or more local regions from the target object image; a feature amount calculation unit configured to calculate a feature amount from each of one or more local regions to recognize the target object; a similarity calculation unit configured to calculate, for each of one or more local regions, a similarity between the feature amounts; and a registration unit configured to, if there is a pair of feature amounts whose similarity is not less than a threshold, register, for each of one or more regions, one of the feature amounts as dictionary data for the target object.

Abstract: An information processing device detects a background region from an image, extracts multiple partial regions from the image, sets multiple local regions for each of the multiple partial regions, selects a local region including a region other than the background region from among the multiple local regions and calculates a local feature amount from the selected local region, and determines a partial region that includes a recognition target object from among the multiple partial regions based on the calculated local feature amount.

Abstract: An object detection apparatus includes an image acquisition unit that acquires image data, a reading unit that reads the acquired image data in a predetermined image area at predetermined resolution, an object area detection unit that detects an object area from first image data read by the reading unit, an object discrimination unit that discriminates a predetermined object from the object area detected by the object area detection unit, and a determination unit that determines an image area and resolution used to read second image data which is captured later than the first image data from the object area detected by the object area detection unit, wherein the reading unit reads the second image data from the image area at the resolution determined by the determination unit.

Abstract: An image recognition apparatus includes an extraction unit configured to extract a feature quantity for each local area from an input image, a conversion unit configured to convert the feature quantity extracted by the extraction unit into a feature quantity indicating a degree with respect to an attribute for each local area, a verification unit configured to verify the feature quantity converted by the conversion unit against a feature quantity of a registered image, and an identification unit configured to identify whether the input image is identical to the registered image by integrating the verification result for each local area acquired by the verification unit.

Abstract: An information processing apparatus includes a face detection unit configured to detect a face of a person from an image; a storage unit configured to store dictionary data which holds information relating to faces and line-of-sight correction data corresponding to respective persons; an authentication unit configured to authenticate a person corresponding to the face detected by the face detection unit, using the information relating to faces in the dictionary data; a line-of-sight detection unit configured to detect information relating to a line of sight from the face detected by the face detection unit; and a line-of-sight correction unit configured to correct the information relating to a line of sight detected by the line-of-sight detection unit, using the line-of-sight correction data in the dictionary data corresponding to the person authenticated by the authentication unit.

Abstract: There is provided an information processing apparatus for detecting a foreground portion from an acquired image. Feature-amount information of a past acquired image and likelihood information indicating a probability that a subject is represented is stored as background-model information. A foreground region is detected based on the likelihood information and a result of comparing the feature amount extracted from the acquired image with the feature-amount information contained in the background-model information. For each of the detected foreground region, a likelihood indicating a probability that the region represents the subject is calculated based on information prepared in advance related to the subject.

Abstract: There are provided an image recognition apparatus and an image recognition method according to which, when registering a face model for a face image, face images are sequentially acquired from frames of a moving image, feature amounts are extracted from the sequentially acquired face images, and a hypersphere defined by Support Vector Data Description (SVDD) is obtained from the group of training samples. Then, training samples in a boundary region of the hypersphere are registered as boundary samples. When performing matching of a face image of a recognition target, the reliability is calculated using the boundary samples, and a person with the highest reliability is output as a recognition result.

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 information processing apparatus acquires registration image data related to an object and input image data related to an object, and matches the acquired registration image data related to the object and each of a plurality of object dictionary data items stored in a storage device. Based on the matching result, the information processing apparatus selects an object dictionary data item relevant to the object related to the registration image data from the plurality of object dictionary data items, and matches the acquired input image data related to the object and the selected object dictionary data item. Based on the matching result, the information processing apparatus determines the object related to the input image data. Based on the determination result, the information processing apparatus updates the selected object dictionary data item. Thus, object recognition is easily and highly accurately performed.

Abstract: An image processing apparatus obtains a difference between a partial region of an input image and a partial region of a background image, stored in a storage device, corresponding to the partial region of the input image, determines whether each partial region of the input image is a moving body region or a background region based on the difference, and combines the partial region of the input image determined as the background region and the partial region of the background image corresponding to the partial region of the input image to update the background image.

Abstract: There is provided a silicon carbide semiconductor device equipped with an ohmic electrode that exhibits both low contact resistance and favorable surface conditions, the silicon carbide semiconductor device including a p-type silicon carbide single crystal, and an ohmic electrode for the p-type silicon carbide single crystal, wherein the ohmic electrode includes an alloy layer containing at least titanium, aluminum and silicon, and ratios of titanium, aluminum, and silicon in the alloy layer are Al: 40 to 70% by mass, Ti: 20 to 50% by mass, and Si: 1 to 15% by mass.

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.