Abstract: A system and method selecting an object from a plurality of objects in a physical environment is disclosed. The method may include framing an object located in a physical environment by positioning an aperture at a selected distance from a user's eye, the position of the aperture being selected such that the aperture substantially encompasses the object as viewed from the user's perspective, detecting the aperture by analyzing image data including the aperture and the physical environment, and selecting the object substantially encompassed by the detected aperture. The method may further include identifying the selected object based on its geolocation, collecting and merging data about the identified object from a plurality of data sources, and displaying the collected and merged data.

Abstract: A method for mapping includes projecting onto an object a pattern of multiple spots having respective positions and shapes, such that the positions of the spots in the pattern are uncorrelated, while the shapes share a common characteristic. An image of the spots on the object is captured and processed so as to derive a three-dimensional (3D) map of the object.

Abstract: A fine pattern, such as a semiconductor integrated circuit (LSI), a liquid crystal panel, and a photomask (reticle) for the semiconductor or the liquid crystal panel, which are fabricated based on data for fabricating the fine pattern such as design data is inspected by a pattern inspection apparatus. The pattern inspection apparatus for inspecting a pattern to-be-inspected uses an image of the pattern to-be-inspected and data for fabricating the pattern to-be-inspected. The pattern inspection apparatus includes a reference pattern generation device configured to generate a reference pattern represented by one or more lines from the data, an image generation device configured to generate the image of the pattern to-be-inspected, a detecting device configured to detect an edge of the image of the pattern to-be-inspected, and an inspection device configured to inspect the pattern to-be-inspected by comparing edges of the image of the pattern to-be-inspected with the one or more lines of the reference pattern.

Abstract: An image processing system includes an image input section, a first character-extracting section, a second character-extracting section and a synthesizing section. The image input section inputs images which are linked to each other in time series manner. The first character-extracting section extracts a character from a first image input by the image input section. The second character-extracting section extracts a character from a second image input by the image input section. The synthesizing section generates a character string in accordance with the character extracted by the first character-extracting section and the character extracted by the second character-extracting section.

Abstract: An information processing apparatus includes clustering means for performing clustering on multiple images so as to more strongly connect the images at a closer distance based on the distances determined by metadata of the images, and grouping means for grouping the images such that the number of images of each group can be equal to or lower than a predetermined number of images in accordance with the strength of connection among the images.

Abstract: The present invention provides a technique of accurately extracting areas of characters included in a captured image. A character extracting device of the present invention extracts each character in an image with compensated pixel values. In more detail, the character extracting device integrates pixel values at each coordinate position in the image along a character extracting direction. Then, the character extracting device predicts the background area in the image based on the integrated pixel value. The compensated pixel values are compensated based on integrated pixel values at the predicted background area from integrated pixel values at each coordinate position.

Abstract: A biometric sensor apparatus uses an infra red light source and a CMOS image sensor. A platen receives a body part and the image sensor receives light transmitted through the body part. A processor determines from the detected through-transmitted light whether the body part is live or is a spoof body part. This determination is based upon a detected variation of the opacity of the body part due to blood flow through the body part. Digital processing of the collected image signal data is performed, such as by smoothing. The sensor may further function as a pattern (such as a fingerprint) sensor for detecting surface patterns on the presented body part and identifying an individual from those sensed patterns.

Abstract: The CT imaging system optimizes its image generation by substantially reducing artifacts caused by a known amount of readout time lag in the X-ray detectors or data acquisition system. Although each detector row takes the same amount of time to read out the signals, the time lag cumulates over the rows as each row is sequentially read out. The back-projection coordinates are correspondingly corrected based upon the above described delay.

Abstract: A biometric data acquisition device for acquiring data of a living body by irradiating the living body with light includes: a light source unit that emits light to the living body; a plurality of light receiving elements that receive transmitted light or reflected light, which is transmitted through the living body or reflects from the living body, respectively, by irradiating the living body with the light from the light source unit; an openable and closable gate provided for each of the plurality of light receiving elements; and an opening and closing control unit that controls opening and closing of the gate so as to make uniform intensities of light received by the plurality of light receiving elements.

Abstract: A computer-implemented pattern recognition method, system and program product, the method comprising in one embodiment: creating electronically a linkage between a plurality of models within a classifier module within a pattern recognition system such that any one of said plurality of models may be selected as an active model in a recognition process; creating electronically a null hypothesis between at least one model of said plurality of linked models and at least a second model among said plurality of linked models; accumulating electronically evidence to accept or reject said null hypothesis until sufficient evidence is accumulated to reject said null hypothesis in favor of one of said plurality of linked models or until a stopping criterion is met; and transmitting at least a portion of the electronically accumulated evidence or a summary thereof to accept or reject said null hypothesis to a pattern classifier module.

Abstract: A method and apparatus for recognizing a gesture in an image processing system. In the apparatus, an input unit receives an image obtained by capturing a gesture of a user using a camera. A detector detects a face area in the input image, and detects a hand area in gesture search areas. The gesture search areas being set by dividing the image into predetermined areas with reference to a predetermined location of the detected face area. A controller sets the gesture search areas, determines whether a gesture occurs in the detected hand area, and selects a detection area with respect to the gesture to generate a control command for controlling an image device. A calculator calculates skin-color information and differential-area information for checking a gesture in the detected hand area. Accordingly, a hand area can be accurately detected, and a gesture can be separated from peripheral movement information, so that mal-functioning caused by gesture recognition can be reduced.

Abstract: A system and method for detecting an object in a high dimensional image space is disclosed. A three dimensional image of an object is received. A first classifier is trained in the marginal space of the object center location which generates a predetermined number of candidate object center locations. A second classifier is trained to identify potential object center locations and orientations from the predetermined number of candidate object center locations and maintaining a subset of the candidate object center locations. A third classifier is trained to identify potential locations, orientations and scale of the object center from the subset of the candidate object center locations. A single candidate object pose for the object is identified.

Abstract: A vehicle surroundings monitoring apparatus capable of recognizing the type of object existing around a vehicle with accuracy.

Abstract: Parametric shape recognition is achieved through a decomposition of shapes into a hierarchy of subshapes ordered by their decreasing restrictions. Instances of each of the subshapes are individually located in the design shape and then reconstructed to form an instance of the entire shape. The basis for the hierarchy of subshapes can be specified by the designer or based on the default parameter relations that come from architectural and engineering knowledge. The levels of the hierarchy are defined so that the most constrained lines of a shape are those lines that the designer intended exactly. These most constrained lines have specified parametric relations to other line segments and those relations, if altered, will compromise the designer's intentions. Conversely, the lowest level of the hierarchy, which contains the least constrained line segments, only implies a specific connectivity between line segments, necessitating a vaster search.

Abstract: The present invention enables permanent biometric authentication without the risk of forgery or the like. The present invention enables living-tissue discrimination as well as biometric authentication. The roughness distribution pattern of deep-layer tissue of the skin covered with epidermal tissue is detected, thereby extracting a unique pattern of the living tissue. Then, biometric authentication is performed based upon the detected pattern. The roughness distribution pattern of the deep-layer tissue of the skin is optically detected using difference in optical properties between the epidermal tissue and the deep-layer tissue of the skin. In this case, long-wavelength light, e.g., near-infrared light is used as illumination light cast onto the skin tissue. A fork structure of a subcutaneous blood vessel is used as the portion which is to be detected, for example. The portion which is to be detected is determined based upon the structure of the fork structure.

Abstract: A movable body circumstance monitoring apparatus includes element for capturing an image of a surrounding of a movable body depending upon movement of the movable body, deriving at least four feature points in a specified flat at the image, tracking the feature points in response to movement of the movable body from a first state to a second state, and specifying relative position and posture of the element for capturing the image at the first and second states in response to first flat coordinates of the feature points at the first state and second flat coordinates of the feature points at the second state based upon a tracking result.

Abstract: Disclosed is a scanning electron microscope (SEM) for realizing high-precision dimension measurement of a sample, such as an ArF exposure photoresist, that requires the measurement of a dimension by a low S/N signal waveform. To this end, partial waveforms (or partial images) of sample signal waveforms (or an images) acquired from a dimension measurement target sample and a sample material of the same kind are registered in advance, a measurement target signal waveform (or an image) obtained from the dimension measurement target sample and the sample registration waveform are combined, and a dimension of the dimension measurement target pattern is calculated based on the combination result.

Abstract: A system and method for recognizing symbols and identifying users or services, including the displaying of an image or video clip on a display device in which identification information is embedded in the image or video clip, the capturing the image or video clip on an imaging device, the transmitting of the image or video clip from the imaging device to a communication network, the transmitting of the image or video clip from the communication network to a processing and authentication server, the processing of the information embedded in the image or video clip by the server to identify logos, alphanumeric characters, or special symbols in the image or video clip, and converting the identified logos or characters or symbols into a digital format to identify the user or location of the user or service provided to the user, and the using of the processed information in digital format to provide one or more of a variety of additional applications.

Abstract: In an apparatus for analyzing a layout of a document, a character candidate element generator generates character candidate elements from black pixel linkage components of a document image. A horizontally oriented line rectangle generator sets a plurality of character candidate elements as a line candidate rectangle, among character candidate elements aligned in horizontal line orientation, when each amount of displacement of the set character candidate elements in a vertical orientation with respect to the horizontal line orientation, is smaller than or equal to a threshold value. A horizontally oriented paragraph-box generator sets a plurality of line candidate elements having approximately the same length as each other in the vertical orientation, as a paragraph candidate element.

Abstract: When labeling is performed for a three-dimensional image, the present invention aims to reduce time required for labeling in the three-dimensional image by three-dimensionally referring connection relationships among image areas. To achieve this object, the following processing is performed. A variable i of label number is initialized to 1 (step S901), and pixels whose pixel value is 1 are searched for (step S902). The first time that a pixel whose pixel value is 1 is detected (step S903), the label number of the pixel is set to i (1) (step S904). When the next pixel (target pixel) whose pixel value is 1 is detected (step S905), if plural pixels having label numbers are detected within a three-dimensional neighboring mask, the smallest label number is assigned as the label number of the target pixel (step S907). If one pixel is detected, the label number is assigned as the label number of the target pixel.