Provided is a segment-block-based handwritten signature authentication system and a method thereof, and more particularly, to a handwritten signature authentication system and a method thereof that enrolls a handwritten signature including handwritten signature characteristics information based on segment blocks disjointed by a user, acquires segment-block-based handwritten signature characteristics information from the handwritten signature upon request for handwritten signature authentication, and performs handwritten signature authentication by comparing the pre-enrolled handwritten signature characteristics information based on segments and the acquired handwritten signature characteristics information.

A method, computer system, and a computer program product for identifying sections in a document based on a plurality of visual features is provided. The present invention may include receiving a plurality of documents. The present invention may also include extracting a plurality of content blocks. The present invention may further include determining the plurality of visual features. The present invention may then include grouping the extracted plurality of content blocks into a plurality of categories. The present invention may also include generating a plurality of closeness scores for the plurality of categories by utilizing a Visual Similarity Measure. The present invention may further include generating a plurality of Association Matrices on the plurality of categories for each of the received plurality of documents based on the Visual Similarity Measure. The present invention may further include merging the plurality of categories into a plurality of clusters.

Systems and techniques are disclosed for labeling objects within an image. The objects may be labeled by selecting an option from a plurality of options such that each option is a potential label for the object. An option may have an option score associated with. Additionally, a relation score may be calculated for a first option and a second option corresponding to a second object in an image. The relation score may be based on a frequency, probability, or observance corresponding to the co-occurrence of text associated with the first option and the second option in a text corpus such as the World Wide Web. An option may be selected as a label for an object based on a global score calculated based at least on an option score and relation score associated with the option.

Provided are an image detection device, an image detection method and a program, which are capable of improving correspondence to a target deformation by optimizing a template shape, when performing target detection using template matching. An image detection device 100 for detecting a target from an input image comprises: a template generation unit 10 that generates a template for detecting a target; a mask generation unit 20 that generates a mask which shields a portion of the template, on the basis of temporal variations of a feature point extracted from an area including the image target; and a detection unit 30 that detects the target from the image using the template a portion of which is shielded by the mask.

Provided are an image detection device, an image detection method and a program, which are capable of improving correspondence to a target deformation by optimizing a template shape, when performing target detection using template matching. An image detection device 100 for detecting a target from an input image comprises: a template generation unit 10 that generates a template for detecting a target; a mask generation unit 20 that generates a mask which shields a portion of the template, on the basis of temporal variations of a feature point extracted from an area including the image target; and a detection unit 30 that detects the target from the image using the template a portion of which is shielded by the mask.

A method and system, the method including receiving semantic descriptions of features of an asset extracted from a first set of images; receiving a model of the asset, the model constructed based on a second set of a plurality images of the asset; receiving, based on an optical flow-based motion estimation, an indication of a motion for the features in the first set of images; determining a set of candidate regions of interest for the asset; determining a region of interest in the first set of images; iteratively determining a matching of features in the set of candidate regions of interest and the determined region of interest in the first set of images to generate a record of matches in features between two images in the first set of images; and displaying a visualization of the matches in features between two images in the first set of images.

In one aspect, it is provided a method comprising receiving an image of a target subject; determining a direction in response to the receipt of the image, the direction being one in which the target subject was likely to move during a time period in the past or is likely to move during a time period in the future; determining a target area within which another image of the target subject can be expected to appear based on the determined direction; and determining if a portion of a subsequent image is outside the determined target area to identify if the subsequent image is one relating to the target subject, wherein the subsequent image is one taken during the time period in the past or during the time period in the future.

A computing device to authenticate works of art comprises a processor programmed to receive test image data corresponding to an image of a test painting to be authenticated; receive a plurality of first artist image data files; receive a plurality of multiple artist image data files; generate a plurality of test painting tiles from the test image data file; generate a plurality of groups of first artist painting tiles; generate a plurality of groups of multiple artist painting tiles; train a classifier to determine one of a plurality of classes for each first artist painting tile and each multiple artist painting tile; use the trained classifier to determine the class for each test painting tile; and determine whether the test painting was likely painted by the first artist according to a percentage of the test painting tiles determined to be the class corresponding to the first artist.

According to one embodiment, an image analysis device includes one or more processors configured to receive input of an image; calculate feature amount information indicating a feature of a region of the image; recognize a known object from the image on the basis of the feature amount information, the known object being registered in learning data of image recognition; recognize a generalization object from the image on the basis of the feature amount information, the generalization object being generalizable from the known object; and output output information on an object identified from the image as the known object or the generalization object.

A medical image diagnostic apparatus according to an embodiment includes processing circuitry configured to determine a plurality of small blocks for each of a plurality of pieces of medical image data, generate a plurality of superpixels corresponding to the plurality of small blocks, assign a label to at least one of the plurality of pieces of medical image data, and perform registration between the plurality of pieces of medical image data using the plurality of superpixels and the label.