Abstract: A defect classification method to classify defects by using a classifier having a binary tree structure based on features of defects extracted from detected signals acquired from a defect inspection apparatus includes a classifier construction process for constructing the classifier by setting a branch condition including defect classes respectively belonging to groups located on both sides of the branch point, a feature to be used for branching, and a discriminant reference, for each branch point in the structure based on instruction of defect classes and feature data respectively associated therewith beforehand. The process includes a priority order specification process for previously specifying target classification performance of purity and accuracy for each defect class, whole and in worst case, with priority order, and an evaluation process for evaluating whether the specified target classification performance under the branching condition is satisfied and displaying a result of evaluation, every item.

Abstract: A method for creating an appearance model of an object includes receiving an image of the object and creating a hierarchical appearance model of the object from the image of the object. The hierarchical appearance model has a plurality of layers, each layer including one or more nodes. Nodes in each layer contain information of the object with a corresponding level of detail. Nodes in different layers of the hierarchical appearance model correspond to different levels of detail.

Abstract: A system and method that provide for decision support and/or training support in crisis decision-making situations are provided. In one implementation, for example, a method identifies patterns from known cases based on information from a crisis event. Each of the known cases includes attributes and at least one outcome. The method also identifies a first subset of the known cases that relate to the identified patterns from the known cases. The method also analyzes the identified patterns to determine a cue that, if answered, will provide a second subset of the known cases including a more converged range of decision outcomes than the first subset.

Abstract: An image processing method is provided for an image processing apparatus which executes processing by allocating a plurality of weak discriminators to form a tree structure having branches corresponding to types of objects so as to detect objects included in image data. Each weak discriminator calculates a feature amount to be used in a calculation of an evaluation value of the image data, and discriminates whether or not the object is included in the image data by using the evaluation value. The weak discriminator allocated to a branch point in the tree structure further selects a branch destination using at least some of the feature amounts calculated by weak discriminators included in each branch destination.

Abstract: A print control method allowing a printing apparatus to perform printing based on a plurality of contents used for outputting a plurality of components to be finally integrated is provided. The CPU determines whether component basis post-processing is set in each of the plurality of contents. The printing sequence is determined such that a first content determined as a content in which the component basis post-processing is set is printed in advance of a second content determined as a content in which the component basis post-processing is not set.

Abstract: A hand-held mobile apparatus and method of quickly displaying online community friends' images applicable thereto are disclosed. The hand-held mobile apparatus includes a network communication module for linking to an online community server; a comparison module for comparing and determining whether data of a web image in the online community server matches data of a local image in a storage unit of the apparatus; a recognition module for determining an image type of the web image when the web image data is different from the local image data; a processing unit for downloading the web image of a first type in a smallest image size or the web image of a second type in an image size matching a screen resolution of the apparatus, and storing the web image in the storage unit as the local image; and a display unit for displaying the local image.

Abstract: A simplified, highly accurate, and real-time constellation pattern recognition and classification device for a software-defined communications apparatus is provided. The constellation pattern recognition and classification device includes an r(k) input, a group of test functions, a means for estimating, a means for calculating, a means for selecting the optimal test function, a means for signal processing, and a means for classifying a pattern that substantially decreases the amount of current constellation pattern calculations and intensive computational requirements and provides a real-time rapid response that improves performance of the software-defined communications apparatus.

Abstract: An image processing apparatus that detects a face area from image information includes a pattern database, a face-direction determining unit, and a face-area detector. The face-direction determining unit determines, as a face direction, a direction in which a face image in image information is upright based on determination pattern information stored in the pattern database. The face-area detector matches the direction of the image information with the direction of the determination pattern information based on the face direction, and detects a face area from the image information.

Abstract: A method is proposed for analyzing an interlaced video signal including a first sequence of fields. A temporal regularity estimation process is applied to the first sequence of fields to compute a first metric. Inputs of the temporal regularity estimation process include pixel values from at least two fields having respective ranks differing by more than one in the sequence. The same temporal regularity estimation process is applied to second and third sequences of fields to compute second and third metrics. The second sequence is derived from the first sequence by swapping fields having ranks of the form 2k and 2k+1 for any integer k, while the third sequence is derived from the first sequence by swapping fields having ranks of the form 2k?1 and 2k. The first, second and third metrics are compared in a determination of the time arrangement of the fields in the first sequence.

Abstract: A system and method for semantic event detection in digital image content records is provided in which an event-level “Bag-of-Features” (BOF) representation is used to model events, and generic semantic events are detected in a concept space instead of an original low-level visual feature space based on the BOF representation.

Abstract: The present application is a method and system of interpreting an image by finding a configuration of multiple variables which optimizes an objective function with a factorizable upper bound, by applying an iterative algorithm that relies on efficient dynamic ordering of candidate configurations, in a priority queue, in a descending order of an upper bound score. As an example, consider a constellation model for an object. It specifies the appearance models for individual parts of objects, as well as spatial relations among these parts. These are combined into a single function whose value represents the likeness of the object in an image. To find the configuration in which the object is present in the image, we maximize this function over all candidate configurations. The purpose of the iterative algorithm mentioned above is to find such optimal configurations efficiently.

Abstract: A face detection method is provided, including: classifying into levels time-wise continuously captured images by increasing/reducing the total number of pixels; selecting sequentially and reading out image data for all of the levels using read-out units of the same size of pixels, or a smaller size of pixels, as those of the image with the smallest size of pixels; carrying out face detection processing by extracting candidate levels in which face image data is present, based on the read-out image data for each of the levels; and, when repeating the face detection processing, setting the number of candidate levels for face detection processing from the second time onward as less than the total number of levels. A digital camera incorporating the face detection method is also disclosed.

Abstract: Described herein is a framework for constructing a hierarchical classifier for facilitating classification of digitized data. In one implementation, a divergence measure of a node of the hierarchical classifier is determined. Data at the node is divided into at least two child nodes based on a splitting criterion to form at least a portion of the hierarchical classifier. The splitting criterion is selected based on the divergence measure. If the divergence measure is less than a predetermined threshold value, the splitting criterion comprises a divergence-based splitting criterion which maximizes subsequent divergence after a split. Otherwise, the splitting criterion comprises an information-based splitting criterion which seeks to minimize subsequent misclassification error after the split.

Abstract: Systems and methods for incorporating restricted access to feature vectors are described. A method is described for storing and accessing feature vectors relating to individuals in digital images. One or more individuals are identified within photos, and feature vectors are generated for individuals in one or more photos. User profiles are downloaded from a database over a network. The feature vectors and downloaded user profiles are grouped. The face tagging system collects tags for the generated grouped feature vectors for generating enhanced user profiles for the individuals, and the enhanced user profiles are stored in a storage resource.

Abstract: In one embodiment, an apparatus may receive at least one image in which multiple targets are represented. The apparatus may assign possible identities to the targets based on probabilities associated with the identities. The apparatus may base a probability of a target being one of the identities, at least in part, on an identity-specific context and on a conditional probability that the target is the identity given that each one of at least two other of the targets is another respective one of the identities. The identity-specific context may be information that relates to a determined identity. The apparatus may identify the targets based on the identities and on the probabilities associated with the identities.

Abstract: A plurality of images inputted in an image signal input portion are divided into a plurality of regions by an image dividing portion, and a feature value in each of the plurality of regions is calculated by a feature value calculation portion and divided into a plurality of subsets by a subset generation portion. On the other hand, a cluster classifying portion classifies a plurality of clusters generated in a feature space into any one of a plurality of classes on the basis of the feature value and occurrence frequency of the feature value. And a classification criterion calculation portion calculates a criterion of classification for classifying images included in one subset on the basis of a distribution state of the feature value in the feature space of each of the images included in the one subset.

Abstract: Assets of raw geo-located imagery can be divided into tiles and coverage masks can be generated for each tile. For each tile, fragments of pixels from coverage masks of neighboring tiles can be extracted and tagged. The fragments can be sorted and stored in a data structure so that fragments having the same tag can be grouped together in the data structure. The fragments can be used to feather the coverage mask of the tile to produce a blend mask. Multi-resolution imagery and mask pyramids can be generated by extracting fragments from tiles and minified (e.g., down-sampled). The minified fragments can be tagged (e.g., by ancestor tile name), sorted and stored in a data structure, so that fragments having like tags can be stored together in the data structure. The fragments can be assembled into fully minified tiles for each level in the pyramid. Input tiles in a first projection are re-projected into a second projection using techniques that minimize distortion in the re-projected imagery.

Abstract: A method for matching an image-form textual string in an image to a regular expression is disclosed. The method includes constructing a representation of the regular expression and generating a candidate string of characters from the image-form textual string. The method further includes ascertaining whether there exists a match between the image-form textual string and the regular expression, the match is deemed achieved if a probability value associated with the match is above a predetermined matching threshold.

Abstract: A method is provided for detection of an airborne contaminant in a atmospheric environment. The method comprises capturing an air sample from the atmospheric environment; separating candidate particles of interest from particles of non interest in the air sample; generating an image of the candidate particles; identifying a contaminant from among the candidate particles by comparing the image of candidate particles with a plurality of stored reference images, each of which reflects a respective identified contaminant; and notifying a remote third party in response to detecting a contaminant from among the candidate particles.

Abstract: This invention provides a vehicle-borne system and method for traffic sign recognition that provides greater accuracy and efficiency in the location and classification of various types of traffic signs by employing rotation and scale-invariant (RSI)-based geometric pattern-matching on candidate traffic signs acquired by a vehicle-mounted forward-looking camera and applying one or more discrimination processes to the recognized sign candidates from the pattern-matching process to increase or decrease the confidence of the recognition. These discrimination processes include discrimination based upon sign color versus model sign color arrangements, discrimination based upon the pose of the sign candidate versus vehicle location and/or changes in the pose between image frames, and/or discrimination of the sign candidate versus stored models of fascia characteristics.

Abstract: A method for facilitating semantic event classification of a group of image records related to an event. The method using an event detector system for providing: extracting a plurality of visual features from each of the image records; wherein the visual features include segmenting an image record into a number of regions, in which the visual features are extracted; generating a plurality of concept scores for each of the image records using the visual features, wherein each concept score corresponds to a visual concept and each concept score is indicative of a probability that the image record includes the visual concept; generating a feature vector corresponding to the event based on the concept scores of the image records; and supplying the feature vector to an event classifier that identifies at least one semantic event classifier that corresponds to the event.

Abstract: Multi-scale processing may be used to reduce the memory and computational requirements of optimization algorithms for image labeling, for example, for object segmentation, 3D reconstruction, stereo correspondence, optical flow and other applications. For example, in order to label a large image (or 3D volume) a multi-scale process first solves the problem at a low resolution, obtaining a coarse labeling of an original high resolution problem. This labeling is refined by solving another optimization on a subset of the image elements. In examples, an energy function for a coarse level version of an input image is formed directly from an energy function of the input image. In examples, the subset of image elements may be selected using a measure of confidence in the labeling.

Abstract: A method for measuring multimedia communication quality is disclosed. The multimedia video communication quality may be objectively reflected through the embedment and extraction of digital watermark under a precondition that the quality of the multimedia video data is not obviously affected. In the invention, each frame of the multimedia video data is uniformly divided into blocks of equal size and watermark data is embedded in each of the blocks, so that the watermark may be uniformly distributed. The multimedia video data are divided into groups, and the watermark is embedded in a part of the frames with equal interval between the frames in each group to reduce the effect of the watermark on the data. The watermark information is directly embedded in the spatial domain of the original video data.

Abstract: Systems and methods for character-by-character alignment of two character sequences (such as OCR output from a scanned document and an electronic version of the same document) using a Hidden Markov Model (HMM) in a hierarchical fashion are disclosed. The method may include aligning two character sequences utilizing multiple hierarchical levels. For each hierarchical level above a final hierarchical level, the aligning may include parsing character subsequences from the two character sequences, performing an alignment of the character subsequences, and designating aligned character subsequences as the anchors, the parsing and performing the alignment being between the anchors generated from an immediately previous hierarchical level if the current hierarchical level is below the first hierarchical level. For the final hierarchical level, the aligning includes performing a character-by-character alignment of characters between anchors generated from the immediately previous hierarchical level.

Abstract: A method and apparatus are provided for effectively predicting a video frame that use all of the advantages of an intra mode and an intra BL mode in multi-layer structure based-video coding. The method includes reconstructing the intra block of a lower layer using the previously reconstructed first neighboring blocks of the intra block; subtracting the first neighboring blocks from previously stored the second neighboring blocks of an upper layer corresponding to the first neighboring blocks; creating a differential predicted block based on a predetermined intra prediction mode by performing intra prediction using virtual differential neighboring blocks that are created as a result of the subtraction; adding the differential predicted block and the reconstructed intra block; and subtracting a predicted block, which is created as a result of the addition, from a block of the upper layer corresponding to the intra block.

Abstract: A system includes a motion detection processor, a motion tracking processor, a people detection processor, a controller, a fusion processor, an appearance model generator processor, a database, a fast search processor, and a matching processor. The motion detection processor, the motion tracking processor, the controller, the people detection processor, the fusion processor, and the appearance model generator processor comprise an analytics pipeline, and the database and the fast search processor comprise a data index pipeline.

Abstract: Kernelized spatial-contextual image classification is disclosed. One embodiment comprises generating a first spatial-contextual model to represent a first image, the first spatial-contextual model having a plurality of interconnected nodes arranged in a first pattern of connections with each node connected to at least one other node, generating a second spatial-contextual model to represent a second image using the first pattern of connections, and estimating the distance between corresponding nodes in the first spatial-contextual model and the second spatial-contextual model based on a relationship with adjacent connected nodes to determine a distance between the first image and the second image.

Abstract: Images are classified as photos (e.g., natural photographs) or graphics (e.g., cartoons, synthetically generated images), such that when searched (online) with a filter, an image database returns images corresponding to the filter criteria (e.g., either photos or graphics will be returned). A set of image statistics pertaining to various visual cues (e.g., color, texture, shape) are identified in classifying the images. These image statistics, combined with pre-tagged image metadata defining an image as either a graphic or a photo, may be used to train a boosting decision tree. The trained boosting decision tree may be used to classify additional images as graphics or photos based on image statistics determined for the additional images.

Abstract: Machine-readable media, methods, apparatus and system for obtaining and processing image features are described. In some embodiments, groups of training features derived from regions of training images may be trained to obtain a plurality of classifiers, each classifier corresponding to each group of training features. The plurality of classifiers may be used to classify groups of validation features derived from regions of validation images to obtain a plurality of weights, wherein each weight corresponds to each region of the validation images and indicates how important the each region of the validation images is. Then, a weight may be discarded from the plurality of weights based upon a certain criterion.

Abstract: When images are classified into categories, which of the categories has important images can be understood easily without a burned on a user. For this purpose, a category weight calculation unit statistically calculates a weight of each of the categories obtained by classification of the images, based on at least one of characteristic quantities comprising the number of images therein found by considering similar images therein, a total photography time thereof, a rate of similar images therein, a rate of human images therein, and an average number of human faces therein.

Abstract: Techniques for positioning images in an electronic document. The images may encode information that can be decoded by devices configured to read the images. An area within the electronic document for positioning the image and a set of one or more colors to be used for the image are determined. The determined area and set of colors are such that the image when positioned in the electronic document blends in with the contents of the electronic document while still being clearly visible for reading by reader devices that are configured read and decode the information encoded by the image.

Abstract: A method of defining a heart region from imaging data is provided. Received imaging data is projected into a first plane. A first threshold is applied to the first plane of data to eliminate data associated with air. A largest first connected component is identified from the first threshold applied data. A first center of mass of the identified largest first connected component is calculated to define a first coordinate and a second coordinate of the heart region. The received imaging data is projected into a second plane, wherein the second plane is perpendicular to the first plane. A second threshold is applied to the second plane of data to eliminate data associated with air. A largest second connected component is identified from the second threshold applied data. A second center of mass of the identified largest second connected component is calculated to define a third coordinate of the heart region.

Abstract: Various systems, methods, and programs embodied in computer-readable mediums are provided for fingerprint liveness detection. In one embodiment, a method for determining fingerprint liveness is provided that comprises receiving a fingerprint image; extracting a region of interest from the fingerprint image; generating a histogram of the region of interest; determining a statistical feature of the histogram; and determining liveness of the fingerprint image based upon the statistical feature.

Abstract: A tag information production apparatus is disclosed which can apply tag information to a main image through a realistic amount of work. A time information acquisition section acquires time information of a main image selected on a working screen, and a key region setting section sets a key region at a position corresponding to a partial region in the main image specified arbitrarily by an operator. An identification information application section applies, to the set key region, region identification information which allows identification between the key region and a peripheral region. A key image production section produces a key image to which time information same as the time information of the main image is applied and in which the region identification information is applied to the key region set through the working screen.

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: An information processing apparatus, which creates a tree structure used by a recognition apparatus which recognizes specific information using the tree structure, including a memory unit which stores data including the information to be recognized and data not including the information so as to correspond to a label showing whether or not the data includes the information, a recognition device which recognizes the information and outputs a high score value when the data including the information is input, and a grouping unit which performs grouping of the recognition devices using a score distribution obtained when the data is input into the recognition devices.

Abstract: Disclosed herein is a production apparatus for index information with link information. The apparatus includes a database in which a corresponding relationship between region identification information applied to a key region which provides a partial region in a main image specified arbitrarily by an operator and link information for accessing to related information of the partial region is listed. The apparatus further includes an information embedding section configured to refer to said database to embed, into index information in which a corresponding relationship between the region identification information applied to the key region and time information is listed, the corresponding link information.

Abstract: An image processing apparatus applying image processing corresponding to a predetermined imaging region of a subject of an image obtained by capturing the imaging region to the image includes an acquisition unit configured to acquire classification information obtained by classifying a plurality of imaging regions according to characteristics of image processing corresponding to each of the imaging regions, an identification unit configured to identify, after identifying which of the groups the imaging region of the image corresponds to, which of the plurality of the imaging regions included in the corresponding group the imaging region of the image corresponds to, based on the image and the classification information, and a processing unit configured to apply the image processing corresponding to the identified imaging region to the image.

Abstract: Apparatus, methods, systems and devices for identifying and tracking a human hand in a video. The steps for identifying the hand includes detecting parallel lines (bars), detecting curved fingertips (curves), grouping the detected parallel lines and curved fingertips according to a parallel line decision tree and a curved fingertip decision tree, respectively, and merging the parallel line group and the curved fingertip group to identify candidate hands.

Abstract: A method of image segmentation using graph-theory techniques, in which pixels of an image are represented by the vertices of a graph. A minimum spanning tree is generated and edges of the tree are successively removed according to a morphological property to leave a spanning forest, trees of which correspond to segments of the image. Selection of edges for removal may depend on an energy function of a tree and on the energy function of trees created by removal of that edge.

Abstract: Provided are systems, apparatuses, methods and techniques for recognizing a pattern within input data, such as a specific object within an image frame. Prior to normalizing the input data, normalization-independent classification is performed, thereby rejecting a number of potential windows early on and resulting in a corresponding reduction in required processing.

Abstract: In image processing according to the prior art, the important part of photographic image data (referred to herein as the object) could not be determined and therefore required human participation. A computer 21 which is the core of image processing calculates an edginess which is an image variation from a differential value of data for adjacent picture elements in a step SA110, and determines object picture elements by selecting only images with a large variation in steps SA120, SA130. As optimum parameters for contrast correction and lightness compensation are calculated from image data for object picture elements in steps SA310-SA330, image processing indicators based on object picture elements are determined, and optimum image processing can be performed automatically.

Abstract: Reference grid information is supplied from a tiling unit to an order control unit. The order control unit generates three control signals on the basis of the reference grid information and outputs them. The first control signal is a signal for controlling the execution order of a vertical low-pass filter and a vertical high-pass filter. The second control signal is a signal for controlling the execution order of a horizontal low-pass filter and a horizontal high-pass filter. The third control signal is a signal for controlling the execution order of a horizontal low-pass filter and a horizontal high-pass filter.

Abstract: A method of detecting a road feature in an image signal derived from an infrared-sensitive camera. The method, in overview, comprises processing an image frame by assigning binary values to pixels in the frame in response to their representative temperature, and then to analyze spatially the binary mask to identify regions of pixels having mutually similar assigned binary values. The road feature is subsequently found from the analysis of the identified regions of mutually similar binary values and a visual indication of the road feature in relation to the image frame provided to the user.

Abstract: A handwriting processing apparatus and method effective for search of, e.g., a document file including handwriting is provided. When a handwriting characters are input to a coordinate input unit as a search key, a corresponding character in a dictionary is recognized for each of the handwritten characters, a search unit searches for a text code stored in a document file storage unit based on a text code of the corresponding character if the corresponding character is recognized and the search unit searches for handwriting trail data stored in a handwriting trail storage unit based on a handwriting trail of the handwriting character if the corresponding character is not recognized, thereby finding a desired document file.

Abstract: A method and apparatus for encoding and/or decoding depth image-based representation (DIBR) data are provided. The encoding method includes: converting 3-dimensional (3D) volume data into adjustable octree data with predetermined labels given to nodes; by referring to the labels, encoding nodes of the adjustable octree from the root node to leaf nodes by a modified breadth-first search (BFS) method allocating priorities among children nodes; and generating a bitstream with predetermined header information and encoded node data. The decoding method includes: extracting header information containing at least resolution information of an object, from a bitstream and decoding the header information; calculating the number of nodes by using the resolution information of the header, and by a modified BFS method allocating priorities among children nodes, decoding each node of a tree from the root node to leaf nodes; and restoring an adjustable tree by using decoded nodes.

Abstract: A method of hierarchical image indexing which extracts representative images of a TV program and generates a hierarchical index image guide of the representative images, and an apparatus therefor. Respective images at predetermined times are extracted from a predetermined program. A hierarchical index is allocated to each extracted image and the indexes are mapped to locations of transport stream packets. A tree of images having the allocated indexes is constructed as a hierarchically indexed Image guide (HIIG). When a stored program is to be reproduced, a location desired to be watched is selected in the HIIG, and from the selected location, reproducing and trick plays (FF, rewind) are enabled such that a user easily searches the program and begins viewing the program at the searched for location.

Abstract: A local bi-gram model object recognition system and method for constructing a local bi-gram model and using the model to recognize objects in a query image. In a learning phase, the local bi-gram model is constructed that represents objects found in a set of training images. The local bi-gram model is a local spatial model that only models the relationship of neighboring features without any knowledge of their global context. Object recognition is performed by finding a set of matching primitives in the query image. A tree structure of matching primitives is generated and a search is performed to find a tree structure of matching primitives that obeys the local bi-gram model. The local bi-gram model can be found using unsupervised learning. The system and method also can be used to recognize objects unsupervised that are undergoing non-rigid transformations for both object instance recognition and category recognition.

Abstract: This invention is to enable retrieving of a content the searcher imagines in mind. The search method includes: obtaining a query brain image representing a brain activity state of a searcher when perceiving or imagining the content to be retrieved; identifying the content corresponding to the query brain image by using a structure associating a content with a brain image representing the brain activity state when perceiving the content; and outputting the content corresponding to the query brain image. Thus, by using the query brain image, without specifically indicating the content such as a drawing, the searcher can extract the pertinent content only by imaging the content.

Abstract: A video annotation method by integrating visual features and frequent patterns is disclosed. This method is featured in integrating a statistical model based on visual features with a sequential model and an association model constructed by data mining skills for automatically annotating unknown videos. This method takes both of visual features and semantic patterns into consideration simultaneously through the combination of three different models so as to enhance the accuracy of annotation.