Abstract: A method and apparatus for identifying a document in a set of stored documents based on a pattern of characteristics in the document is presented. A digital image including at least a portion of the a document is acquired. A pattern of characteristics is then identified in the digital image. The pattern is matched to the set of stored documents to identify the document in the digital image from the set of stored documents.

Abstract: Systems (100) and methods (300) for efficient spatial feature data analysis. The methods involve simultaneously generating chip images using image data defining at least a first image and video chips using video data defining at least a first video stream. Thereafter, an array is displayed which comprises grid cells in which at least a portion of the chip images is presented, at least a portion of the video chips is presented, or a portion of the chip images and a portion of the video chips are presented. Each chip image comprises a panned-only view, a zoomed-only view, or a panned-and-zoomed view of the first image including a visual representation of at least one first object of a particular type. Each of the video chips comprises a segment of the first video stream which include a visual representation of at least one second object of the particular type.

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: A method of converting an image from one form to another form by a conversion apparatus having a memory and a processor, the method including the steps of receiving a captured image, extracting at least one image dimension attribute from the image, calculating at least one dimension attribute of the image based on the image dimension attribute, modifying the image based on the calculated dimension attribute and the extracted dimension attribute, and displaying the modified image on a display unit.

Abstract: Object recognition apparatus and methods useful for extracting information from an input signal. In one embodiment, the input signal is representative of an element of an image, and the extracted information is encoded into patterns of pulses. The patterns of pulses are directed via transmission channels to a plurality of detector nodes configured to generate an output pulse upon detecting an object of interest. Upon detecting a particular object, a given detector node elevates its sensitivity to that particular object when processing subsequent inputs. In one implementation, one or more of the detector nodes are also configured to prevent adjacent detector nodes from generating detection signals in response to the same object representation. The object recognition apparatus modulates properties of the transmission channels by promoting contributions from channels carrying information used in object recognition.

Abstract: Systems and methods are provided for providing patch size adaptation for patch-based image enhancement operations. In one embodiment, an image manipulation application receives an input image. The image manipulation application compares a value for an attribute of at least one input patch of the input image to a threshold value. Based on comparing the value for the to the threshold value, the image manipulation application adjusts a first patch size of the input patch to a second patch size that improves performance of a patch-based image enhancement operation as compared to the first patch size. The image manipulation application performs the patch-based image enhancement operation based on one or more input patches of the input image having the second patch size.

Abstract: Systems and methods are provided for providing learned, piece-wise patch regression for image enhancement. In one embodiment, an image manipulation application generates training patch pairs that include training input patches and training output patches. Each training patch pair includes a respective training input patch from a training input image and a respective training output patch from a training output image. The training input image and the training output image include at least some of the same image content. The image manipulation application determines patch-pair functions from at least some of the training patch pairs. Each patch-pair function corresponds to a modification to a respective training input patch to generate a respective training output patch. The image manipulation application receives an input image generates an output image from the input image by applying at least some of the patch-pair functions based on at least some input patches of the input image.

Abstract: A system and method for identifying an unknown individual from a plurality of enrolled individuals is provided. In an embodiment, the method comprises comparing at least two parameters of the unknown individual to at least two enrolled parameters of the enrolled individuals. The method then determines a score correlating to the closeness of the comparison and then stores the score.

Abstract: In the case of collecting samples, it is difficult to select a representative point of a target area. Thus, the samples are collected from certain positions, resulting in generation of variations of data. The target area is specified on an image to extract features from the target area. Further, clustering is performed for the features on a feature space to obtain representative features, and the obtained representative features are extracted as sampling points.

Abstract: A character detection apparatus is provided that detects, from an image including a first image representing a character and a second image representing a translucent object, the character. The character detection apparatus includes a calculating portion that, for each of blocks obtained by dividing an overlapping region in which the first image is overlapped by the second image, calculates a frequency of appearance of pixels for each of gradations of a property, and a detection portion that detects the character from the overlapping region based on the frequency for each of the gradations.

Abstract: An image processing device for recognizing an object corresponding to a registered image registered beforehand from an imaged image, comprising: an obtaining unit configured to obtain the imaged image; a recognizing unit configured to recognize an object corresponding to the registered image from the imaged image; and a detecting unit configured to detect, based on a registered image corresponding to an object recognized from the imaged image thereof, an area where another object is overlapped with the object corresponding to the registered image thereof.

Abstract: A fingerprint identification data card and an electronic device are provided. The data card includes a case, a circuit board located in the case, an interface, and a fingerprint identifier. The case has a hole, the interface passes through the hole and the interface is connected with the circuit board, and the fingerprint identifier is disposed in the case and is connected with a processor on the circuit board in the case. It can be seen that, before using the data card, a user is required to input a fingerprint through the fingerprint identifier, and the user can use the data card only after passing authentication.

Abstract: In one embodiment, L dimensional images are trained, mapped, and aligned to an M dimensional topology to obtain azimuthal angles. The aligned L dimensional images are then trained and mapped to an N dimensional topology to obtain 2N vertex classifications. The azimuthal angles and the 2N vertex classifications are used to map L dimensional images into 0 dimensional images.

Abstract: A method for inspecting a manufactured product includes applying a first test regimen to the manufactured product to identify product defects. The first test regimen produces a first set of defect candidates. The method further includes applying a second test regimen to the manufactured product to identify product defects. The second test regimen produces a second set of defect candidates, and the second test regimen is different from the first test regimen. The method also includes generating a first filtered defect set by eliminating ones of the first set of defect candidates that are not indentified in the second set of defect candidates.

Abstract: Provided are a filtering method and apparatus for removing blocking artifacts and ringing noise. The filtering method includes transforming video data on a block-by-block basis, and detecting the presence of an edge region in the video data by checking the distribution of values obtained by the transformation. Accordingly, it is possible to completely remove blocking artifacts and/or ringing noise by more effectively detecting the presence of an edge region in video data.

Abstract: According to a conventional image classification device that extracts a feature from an image and classifies the image with use of the extracted feature, in the case where one image and another one image, which are included in an image group, each have a different feature, the one image and the other one image might be each classified into a different category. In order to solve this problem, an image classification device relating to the present invention calculates, with respect to each of persons appearing in a plurality of images included in an image group which have been photographed with respect to one event, a main character degree that is an index indicating an important degree in units of image groups, and classifies the images into any one of different classification destination events in units of image groups based on the calculated main character degrees.

Abstract: This invention relates to a secured identification medium and a method for securing such a medium. The secured identification medium comprises an integrated circuit and, printed on one side, identification information (Ip) about the holder of the medium. It further comprises a set of characteristic attributes Att(Ipi) of the identification information, generated from a capture (Ipi) of the identification information and an extraction algorithm. The set of characteristic attributes of the printed analog image is stored in the integrated circuit and is designed to be compared, during an authentication stage, with a second set of characteristic attributes of the same printed image on the medium.

Abstract: It is an object to obtain an image of a wafer that is suitable for a defect inspection in an efficient manner. It is judged whether or not an average gray level of an image of a wafer W that is an inspection target and that has been imaged by the light receiving part 2 is in the defect detectable range. A control processing part 6a is configured to modify an exposure time in imaging the wafer W and to obtain an image of the wafer W again by the light receiving part 2 in the case in which it is decided that an average gray level of an image of the wafer W is not in a defect detectable range, and an image processing part 6b is configured to carry out a defect inspection based on an image of the wafer W in the case in which it is decided that an average gray level of the image of the wafer W is in the defect detectable range.

Abstract: An apparatus for providing pattern detection may include a processor. The processor may be configured to iteratively test different models and corresponding scales for each of the models. The models may be employed for modeling parameters corresponding to a visually detected data. The processor may be further configured to evaluate each of the models over a plurality of iterations based on a function evaluation of each of the models, select one of the models based on the function evaluation of the selected one of the models, and utilize the selected one of the models for fitting the data.

Abstract: Biometric authentication technology, in which biometric data is maintained for a group of people. The biometric data includes sorted similarity scores, where each of the sorted similarity scores is computed to represent similarity between a corresponding biometric image and a reference image. A biometric verification system accesses a biometric image of at least a portion of a person, accesses the reference image, and computes a similarity score that represents similarity between the accessed biometric image and the reference image. The biometric verification system searches the sorted similarity scores included in the biometric data using the computed similarity score and outputs a result based on the searching.