Abstract: A feature area extracting section extracts an area having a unique feature in an image input to an image selection support apparatus. A specific area feature collating and determining section determines whether or not the area having a feature and extracted by the feature area extracting section is a specific area. A specific area image reading section decides a rectangular area including the specific area, and reads image information of the rectangular area. The specific area image reading section has at least one of an enlargement displaying section which enlarges and displays the image information read by the specific area image reading section, a thumbnail display section which reduces and displays the input image, and an original image displaying section which enlarges and displays the input image.

Abstract: In a scene recognition photographing device of the present invention, a feature quantity of an acquired image acquired from an image pickup element is calculated from the acquired image. Plural types of reference feature information having a feature quantity serving as a reference at the time of determining a composition are stored as a database in an internal memory or a storage device. Moreover, a camera control unit retrieves reference feature information having a feature quantity similar to the feature quantity of the acquired image from among the reference feature information by comparing the calculated feature quantity and the reference feature information. Then, information relating to composition is displayed on a display device on the basis of a result of comparison between the acquired image and the retrieved reference feature information.

Abstract: An electronic camera detects a person's face image from an object image obtained by photographing an object, executes an enlarging process on the detected face image so as to obtain a face image whose face size is suitable, and displays the face image which is enlarged into the suitable size on a display device. When a plurality of people are present on the object image, the enlarged face images are switched by an image operating switch. As a result, the switched face image is displayed on the display device.

Abstract: An electronic camera of the present invention has a function for photographing combined images including plural continuously photographed images. A continuous photographing mode according to a moving subject is selected by a photographing mode selection unit. A continuous photographing interval, a maximum continuous photographing number, and a number of precaptured images to be obtained are set by a system controller according to the continuous photographing mode selected by the photographing mode selection unit. When a release button is depressed, continuous photographing is carried out under the photographing conditions of the continuous photographing mode selected by the mode selection unit.

Abstract: An imaging apparatus comprises an optical magnification changing mechanism which optically changes a magnification of an image, and an electronic magnification changing mechanism which reduces or expands a magnification with respect to image data by signal processing, the imaging apparatus providing a magnification-changed image according to a predetermined magnification based on the optical magnification changing mechanism and the electronic magnification changing mechanism. The optical magnification changing mechanism has at least two magnifications W and T (W<T) which are discrete each other, and has a switching mechanism which, when a predetermined magnification M (W<M<T) has been set, switches an image obtained by the magnification W and an expanding conversion using the electronic magnification changing mechanism and an image obtained by the magnification T and a reducing conversion using the electronic magnification changing mechanism.

Abstract: An imaging apparatus has the function of an optical zoom which optically converts the magnification of an image and the function of an electronic zoom which changes the size of an image by electrical signal processing. The function of the electronic zoom at least operates when the optical zoom is not set at the telephoto end. A total magnification is determined by changing magnification by the optical zoom and changing magnification by the electronic zoom. A pixel count s1 of an electronic imaging device, a pixel count s2 of a rectangle including the pixels on an imaging device which are used by the electronic zoom, and a pixel count s3 of an output satisfy s1?s2>s3 or s1>s2?s3.

Abstract: There are performed three types of object shooting, i.e., a projection pattern shooting using a pattern including both characterization of a stripe based on a color and characterization based on a gradation of the same component, a flash shooting without a pattern and a non-flash shooting without a pattern. A two-dimensional image information generation portion corrects the influence of a surface reflectivity of an object or external light from the three types of images, and estimates a pattern structure using the characteristic based on a color with respect to an object having a white-based color or a low-saturation color and based on a gradation with respect to an object having a high-saturation color. A depth calculation portion specifies the correspondence relationship between the estimated pattern structure and information of the projected pattern, and calculates a depth of each part of the object based on a result of specification.

Abstract: An imaging apparatus has an imaging element which converts an optically formed image to an electrical signal by photoelectric conversion and acquires image data. The imaging apparatus comprises an optical magnification changing mechanism which optically changes a magnification of an image, and an electronic magnification change mechanism which reduces or expands a magnification with respect to image data by signal processing, and provides a magnification-changed image according to a predetermined magnification based on the optical magnification changing mechanism and the electronic magnification change mechanism. The optical magnification changing mechanism is configured so that a magnification is discrete and a focal position changes together with a focal distance.

Abstract: An imaging apparatus is disclosed. An imaging device acquires an object image as pixel data in accordance with photoelectric conversion. A readout region setting unit sets a region in which image data is to be read out from the imaging device. A readout unit reads out the image data from the readout region. An optimal position calculating unit calculates a position optimal for imaging according to the position and size of a readout region set by the readout region setting unit. An adjusting mechanism drives an imaging surface of the imaging device at the optimal position calculated by the optimal position calculating unit.

Abstract: A 3D image acquisition apparatus comprises a pattern projection section which projects a pattern on an object to be measured, an imaging section which is disposed at a distance from the pattern projection section and images the object on which the pattern has been projected, and a depth calculation section which detects the projection pattern projected on the object on the basis of an image acquired by the imaging section, collates the detected pattern and the projected pattern, and calculates a depth of respective parts of the object on the basis of the correspondency of the collation. The projected pattern is stripes/matrix formed by alternately arranging areas with local maximum/minimum luminance values. Thus, stripes/matrix boundaries can be exactly extracted from the pattern projection image, and correct decoding is performed from the encoded projection image even where the object is not a white-based color one or a low-saturation color one.

Abstract: A learning type image classification apparatus is capable of classifying a plurality of images flexibly. A region clipping mode selection section is capable of selecting a mode of clipping regions from images from a plurality of candidates. The region clipping execution section clips regions from images in a mode selected by the selection section of the region clipping mode.

Abstract: An image segmentation apparatus divides an image into plural regions according to feature quantities of pixels for composing the image, by a programmed computer. A divider divides the image into plural regions by using the separation degree of feature quantities of pixels for composing the image. A separation degree operator determines the separation of feature quantities between interior and exterior region, according to the dissimilarity of feature quantities of pixels for enclosing the boundary of plural regions divided by the divider. A changer changes the alienation degree of feature quantities of pixels enclosing the boundary between the interior and exterior region in a specific condition, by using the alienation degree of feature quantities between interior and exterior region calculated by the alienation degree operator. The divider divides the image into plural regions by using changed separation degree.

Abstract: There are performed three types of object shooting, i.e., a projection pattern shooting using a pattern including both characterization of a stripe based on a color and characterization based on a gradation of the same component, a flash shooting without a pattern and a non-flash shooting without a pattern. A two-dimensional image information generation portion corrects the influence of a surface reflectivity of an object or external light from the three types of images, and estimates a pattern structure using the characteristic based on a color with respect to an object having a white-based color or a low-saturation color and based on a gradation with respect to an object having a high-saturation color. A depth calculation portion specifies the correspondence relationship between the estimated pattern structure and information of the projected pattern, and calculates a depth of each part of the object based on a result of specification.

Abstract: A feature area extracting section extracts an area having a unique feature in an image input to an image selection support apparatus. A specific area feature collating and determining section determines whether or not the area having a feature and extracted by the feature area extracting section is a specific area. A specific area image reading section decides a rectangular area including the specific area, and reads image information of the rectangular area. The specific area image reading section has at least one of an enlargement displaying section which enlarges and displays the image information read by the specific area image reading section, a thumbnail display section which reduces and displays the input image, and an original image displaying section which enlarges and displays the input image.

Abstract: An image detection apparatus includes a filter operation unit for conducting an operation of calculating a synthetic product between inputted image data and a plurality of filters, wherein respectively, the filters differ in direction. And having respective orientations a directional balance operation unit includes an angle calculation unit for obtaining an angle made between a vector whose components are a plurality of outputs of the filter operation unit for each directions and a reference vector whose components are equal to each other. A rounded convex region detection unit detects rounded convex regions within the inputted image based on an output of the directional balance calculation unit.

Abstract: A 3D image acquisition apparatus comprises a pattern projection section which projects a pattern on an object to be measured, an imaging section which is disposed at a distance from the pattern projection section and images the object on which the pattern has been projected, and a depth calculation section which detects the projection pattern projected on the object on the basis of an image acquired by the imaging section, collates the detected pattern and the projected pattern, and calculates a depth of respective parts of the object on the basis of the correspondency of the collation. The projected pattern is stripes/matrix formed by alternately arranging areas with local maximum/minimum luminance values. Thus, stripes/matrix boundaries can be exactly extracted from the pattern projection image, and correct decoding is performed from the encoded projection image even where the object is not a white-based color one or a low-saturation color one.

Abstract: A learning type image classification apparatus is capable of classifying a plurality of images flexibly. A region clipping mode selection section is capable of selecting a mode of clipping regions from images from a plurality of candidates. The region clipping execution section clips regions from images in a mode selected by the selection section of the region clipping mode.

Abstract: A vector normalizing apparatus in which information concerning the norm of the original vector is not lost by normalization, and which needs no device that divides vector components by norm. The apparatus includes a vector input device (1) for entering a vector. An additional component calculating device (2) receives the vector entered through the vector input device (1) and calculates an additional component to be added to the vector such that norm of the vector after the addition of the component becomes constant. A vector component adding device (3) adds an output from the additional component calculating device (2) as a component of the entered vector. A normalized vector output device (4) outputs the vector having the component added thereto.

Abstract: A recursive neural net including processing elements (1) each having a linear saturated function as an input/output function. The elements (1) are divided into a plurality of blocks (2), and the states of the elements (1) are asynchronously updated block by block while being synchronously updated within each block (2). Since convergence is ensured for any symmetric synaptic matrix (W) by selecting a step-size for each particular problem, the neural net can be applied to any optimization problem. In addition, a neural net system is composed of an optical computing unit (201 to 205) performing a vector matrix calculation using light, a threshold processing unit (206) performing a threshold processing operation, a coefficient multiplying unit (209) performing a step-size processing operation, a saturated linear computing unit (207) performing a saturated linear function operation, and a block control unit (208) performing selection of a block to be updated and state updating therefor.