Abstract: An image registration system for aligning first and second images. The novel system includes a first system for extracting a region of interest (ROI) from each image and a second system for coarsely aligning the regions of interest. The first system determines the size and location of the ROI based on the number of features contained within the region. The size of the ROI is enlarged until a number of features contained in the ROI is larger than a predetermined lower bound or until the size is greater than a predetermined upper bound. The second system computes a cross-correlation on the regions of interest using a plurality of transforms to find a coarse alignment transform having a highest correlation. The image registration system may also include a third system for performing sub-pixel alignment on the regions of interest.

Abstract: A data clustering method, a data clustering device using the same, and an image processing apparatus and a data processing apparatus equipped with the data clustering device are provided. The method includes sorting a plurality of data point to be clustered and generating a processing sequence based on the sorting, wherein each of the data point has at least one feature value. The method also includes using a non-iterative mechanism to cluster the data points into a plurality of data clusters according to the processing sequence. The method further includes optimizing the generated data clusters. Accordingly, the data clustering method can fast cluster the data points.

Abstract: Presented is a method of automatically performing an action, based on graphical input. The method comprises: receiving, for a user, an input image; comparing the input image with the contents of a user-customized database comprising a plurality of records, each record representing a predefined class of image, wherein the user has previously associated records in the database with respective specified actions; attempting to recognize the image, based on the similarity of the input image to one of the predefined classes of image represented in the user-customised database; and if the image is recognized, performing the action previously associated by the user with the class. Also presented is apparatus for recognizing an image and a method of constructing a user-customized database.

Abstract: A dense guide image or signal is used to inform the reconstruction of a target image from a sparse set of target points. The guide image and the set of target points are assumed to be derived from a same real world subject or scene. Potential discontinuities (e.g., tears, edges, gaps, etc.) are first detected in the guide image. The potential discontinuities may be borders of Voronoi regions, perhaps computed using a distance in data space (e.g., color space). The discontinuities and sparse set of points are used to reconstruct the target image. Specifically, pixels of the target image may be interpolated smoothly between neighboring target points, but where neighboring target points are separated by a discontinuity, the interpolation may jump abruptly (e.g., by adjusting or influencing relaxation) at the discontinuity. The target points may be used to select only a subset of the discontinuities to be used during reconstruction.

Abstract: There are provided: a pattern detection process section for extracting a partial image made of pixels including a target pixel from input image data; a rotated image generating section for generating a self-rotated image by rotating the partial image; and a matching test determination section for determining whether an image pattern included in the partial image matches an image pattern included in the self-rotated image. When it is determined that matching exists, a target pixel in the partial image or a block made of pixels including the target pixel is regarded as a feature point. Consequently, even when image data has been read while skewed with respect to a predetermined positioning angle of a reading position of an image reading apparatus or image data has been subjected to enlarging, reducing etc., a feature point properly specifying the image data can be extracted regardless of skew, enlarging, reducing etc.

Abstract: A method and an apparatus search an image using a feature point. The image search method extracts at least one feature point from an image and describes the extracted at least one feature point in stages, thereby generating a hierarchical feature point descriptor. In addition, the method may search for information matching the feature point descriptor from a local database (DB) included in a terminal or a remote DB included in a server.

Abstract: A method and system of determining a radial distance (R), an angular position (?), and an axial position (Z) of a marker identified in a sequence of projection images. A marker three-dimensional localization module (executable by the electronic processing unit) obtains a sequence of images based on image data generated by a scanner. Each image in the sequence of images represents an angle of rotation by the scanner and includes a marker point position. The behavior of first values and second values of the marker point positions are analyzed through the sequence of images to determine the radial distance of the marker, the angular position of the marker, and the axial position of the marker allowing for rapidly detecting and localizing external markers placed on a patient in projection images.

Abstract: There are provided: a pattern detection process section for extracting a partial image made of pixels including a target pixel from input image data; a displaced image generation section for generating a self-displaced image by displacing at least a part of the partial image through a predetermined method; and a matching test determination section for determining whether an image pattern included in the partial image matches an image pattern included in the self-displaced image or not. When the matching test determination section determines that the matching exists, a target pixel in the partial image or a block made of pixels including the target pixel is regarded as a feature point. Consequently, even when image data is subjected to a process such as enlarging and reducing, it is possible to extract a feature point that properly specifies the image data regardless of the enlarging/reducing process.

Abstract: According to one embodiment, a search skip region setting function generation method includes associating, detecting, and generating. The associating associates a template used to search a model image for an object with a designated search point on the model image, and detects a designated search point similarity between the designated search point and the template. When the designated search point similarity exceeds an object detection determination threshold, the detecting detects surrounding search point similarities between a plurality of surrounding search points around the designated search point on the model image and the template. The generating generates a function required to set a search skip region of the object based on relative positions between the object and the template, which are estimated based on a distribution of the surrounding search point similarities.

Abstract: Provided is a marker generation device which has a measurement means, an invariant feature conversion means, a singular feature selection means, and a marker generation means. The measurement means measures a change in posture of an object in a background image on the basis of the image. The invariant feature conversion means indicates feature points extracted from the background image in an invariant feature space by means of a predetermined conversion process in accordance with the change in posture. The singular feature selection means selects, as a singular feature, a part in which the feature points are not indicated in the invariant feature space. The marker generation means generates a marker with the use of the singular feature.

Abstract: Embodiments of an image registration system and method registering corresponding images of a deformable surface are generally described herein. In some embodiments, image features of the corresponding images are converted to point features, the point features from each corresponding image are sorted based on one or more attributes of the point features, and a plurality of three-point sets are generated for each image from a selected portion of the sorted point features. Each three-point set defines a triangle. Matching triangles may be identified from the corresponding images. The corresponding point features of the matching triangles represent corresponding image features providing for at least local image registration.

Abstract: Provided is a marker judgment device which has a feature storage means and a feature comparison means. The feature storage means disposes feature points extracted from an image in a predetermined space, sets parts in which the number of feature points in the predetermined space is equal to or less than a predetermined number as singular features, and stores the singular features and feature points extracted from an existing mark. The feature comparison means disposes the feature points extracted from the existing mark in the predetermined space, and judges that the existing mark is capable of being used as a marker which is detectable from the image, when the number of feature points that coincide with the singular features is equal to or more than a predetermined number.

Abstract: An image processing device includes: an interest area detector that detects interest areas included in a time-series image group captured in time series; a calculation processing unit that calculates feature amounts indicative of features of the interest areas; an area classification unit that classifies the interest areas into area groups, based on the feature amounts of the interest areas and time-series positions of time-series images including the interest areas; a group feature amount calculation unit that calculates a group feature amount indicative of a feature of each of the area groups; an area selection unit that selects one or more representative areas of the interest areas belonging to the area groups, from among the area groups; and a representative image output unit that outputs one or more representative images including the representative areas in the time-series image group.

Abstract: An action analysis apparatus includes an acquiring unit that acquires moving image data including a series of frame image data obtained by imaging a human body and environmental information in a period when the moving image data is imaged, a unit that detects at least one image area in which a predetermined portion of the imaged human body is imaged in the frame image data and generates and stores information to identify the detected image area, a unit that (i) generates feature quantity information, (ii) generates information to identify frames of the moving image data imaged at a timing at which the feature quantity information satisfies a predetermined condition, (iii) obtains a length of continuous timings at which a length of the feature quantity information exceeds the predetermined condition based on to generated information, and (iv) stores the information.

Abstract: A method of and system for computing control points in a test target are described herein. The method and system utilize symmetry to test pixel locations in a raster scan fashion, then a computed Sum of Absolute Differences or a Sum of Squared Difference value is stored at the pixel locations, which enables identification of local minimum in the resulting surface. The local minimum are control point locations.

Abstract: Over the past few years there has been a dramatic proliferation of digital cameras, and it has become increasingly easy to share large numbers of photographs with many other people. These trends have contributed to the availability of large databases of photographs. Effectively organizing, browsing, and visualizing such .seas. of images, as well as finding a particular image, can be difficult tasks. In this paper, we demonstrate that knowledge of where images were taken and where they were pointed makes it possible to visualize large sets of photographs in powerful, intuitive new ways. We present and evaluate a set of novel tools that use location and orientation information, derived semi-automatically using structure from motion, to enhance the experience of exploring such large collections of images.

Abstract: A method of determining change in a state of an object using images of the object, the method including providing a first image and a second image of the object, the first image and the second image being spaced apart in time, performing a plurality of pixel-based change detection algorithms to obtain a plurality of output difference products/images containing change information and pseudo change information, combining the plurality of output difference products to form a hybrid output difference product and thresholding the output difference product to detect changes in the object.

Abstract: A method for determining feature point locations in an image performs a first search in a predetermined first search area to search for locations of plural feature points in the image, corrects the locations of the plural feature points based on a geometric layout relationship among the plural feature points searched for, sets a second search area based on the corrected location of each of the feature points, and performs a second search in the second search area to search for the location of each of the feature points. Then, the method determines reliability of the location of each feature point searched for by the second search and selects one of the corrected location and the location searched for by the second search, as a location of the feature point.

Abstract: Methods and systems of recognizing images may include an apparatus having a hardware module with logic to, for a plurality of vectors in an image, determine a first intermediate computation based on even pixels of an image vector, and determine a second intermediate computation based on odd pixels of an image vector. The logic can also combine the first and second intermediate computations into a Hessian matrix computation.

Abstract: A system and method for identifying an image based on singular value decomposition is provided. The system includes: a feature point extracting module for extracting at least one of feature points from an input image using strength of a Gaussian curvature of each pixel from the input image; an identifier detecting module for detecting a local identifier based on SVD (singular value decomposition) for blocks adjacent to the extracted feature points; and a matching module for determining whether an image is duplicated or not by comparing the detected local identifier from the identifier detecting module with an image database storing at least one of images.

Abstract: In accordance with an embodiment, a method of authenticating images includes electronically receiving an anchor image and a query image, performing a feature point extraction of an anchor image, and performing a feature point extraction of a query image. The method also includes clustering feature points of the anchor image and feature points of the query image, where clustering includes determining matching feature points, determining outlier feature points, and excluding outlier feature points. Whether the anchor image is similar to the query image is determined based on a distance between the feature points of the anchor image and the feature points of the query image. If the anchor image is similar to the query image, possible tampered areas of the query image based on the outlier feature points are identified.

Abstract: A pattern evaluation method includes: acquiring data of a design pattern for an evaluation pattern to detect a first edge of the design pattern; acquiring an image of the evaluation pattern to detect a second edge of the evaluation pattern; dividing the first edge into first linear parts and first corner parts; performing matching of the first and second edges to obtain correspondence between the first and second edges; dividing the second edge into second linear parts and second corner parts based on the correspondence between the first and second edges; and evaluating the evaluation pattern based on at least one of the second linear parts and the second corner parts.

Abstract: Image processing methods are described that include segmenting boundaries of a region of interest (ROI) and identifying one or more control points, in each of multiple images of the same object, region, or location. The coordinates of each image are transformed from image coordinates into a coordinate frame relative to the control point or points. Image data is resampled and filtered and/or averaged. One or more material properties can be calculated from the resampled and filtered image data and then displayed. Alignment of unregistered image data of multiple images of the same object, region, or location is provided. Applications are described for medical imaging.

Abstract: An adding metadata apparatus includes a first acquisition unit which acquires a first image, first metadata, and a first position within the first image, the first position being for displaying the first metadata; an extraction unit which extracts local features from the first image; a calculation unit which searches for a group of the local features within a predetermined distance from the first position, and calculates a representative point of the group; a search unit which matches the first image with a plurality of images stored in a database by using the local features, and searches for a second image which coincides with the local features; and a registration unit which calculates a second position, within the second image, corresponding to the representative point, and registers the second position and the first metadata as metadata for the second image.

Abstract: An image, represented by an ordered set of elements (xi) each having a value is analysed in order to detect vanishing points. The method comprises, for each of a plurality of root positions (x0), repeatedly performing the steps of: (i) selecting a first plurality of elements (xi) from the ordered set; (ii) for each selected element (xi), selecting a second element (ui) such that the selected second element has a vector position relative to the root position that is scaled by a factor (?) in comparison with the position of the first selected element; (iii) determining whether the selected elements meet a match criterion requiring that the value of each of the first elements is similar to the value of the corresponding second element; and (iv) in the event of a match, updating a similarity score (H) in respect of that root element. Once these scores have been found, they can be examined a part of the image corresponding to a peak value of the similarity score.

Abstract: Disclosed is a pattern noise removal device for removing background pattern noise having periodicity from a digital image, which includes a candidate pixel extracting module for extracting candidate pixels that constitute the background pattern noise from the pixels in the image on the bases of the concentration of each of the pixels, a dot pattern feature extracting module for extracting the feature of a dot pattern formed by each of the candidate pixels and the peripheral neighborhood pixels among the extracted candidate pixels, a dot pattern area extracting module for extracting a dot pattern area including the candidate pixels of the periodicity and the neighborhood pixels, which have the feature of the dot pattern, and a periodic pattern noise removal module for removing the candidate pixels of the periodicity and the neighborhood pixels, which are included in the dot pattern area, as the background pattern noise.

Abstract: An image processing method and a system for processing the same are provided. The image processing method includes the following steps. A first image having several first areas and a second image having several second areas are provided. Each first area has a first feature point having the largest or the smallest grey value in the first area. Each second area has a second feature point having the largest or the smallest grey value in the second area. A first relationship between the first feature points and a second relationship between the second feature points are created. The first and the second feature points are paired by a microprocessor according to the first and the second relationship.

Abstract: A technique of efficiently extracting and synthesizing an object image from a plurality of images captured at different image magnifications. An image processing method of the present invention includes the steps of generating a first background image corresponding to a first image captured at a predetermined image magnification, extracting a first object image from the first image, generating a second background image corresponding to a second image captured at an image magnification higher than the predetermined image magnification, based on the first background image and the first object image, and extracting a second object image from the second image and the second background image.

Abstract: A system for the identification of feature points in low contrast images.

Abstract: A system and method for determining inflection points in an image of an object includes obtaining the image of the object, performing binary image processing on a border of the image to obtain border points, selecting a predetermined number of the border points to fit a straight line, calculating a vertical distance between each selected border point and the straight line, and obtaining a total distance. The method further includes adding a new border point to the selected border points if the total distance is less than a predetermined value, so as to fit a new straight line and do a loop cycle, otherwise, regarding a last border point of the selected border points as an inflection point, and sequentially selecting the predetermined number of other border points to fit another new straight line.

Abstract: Described is a system for anomaly detection to detect an anomalous object in an image, such as a concealed object beneath a person's clothing. The system is configured to generate a subspace model for a normal class using training images. The normal class represents normal objects in a common class. The system receives a novel image having an object in the common class. A set of geometric landmarks are identified in the object in the novel image for use in registering the image. The novel image is registered by warping the image so that the geometric landmarks coincide in the novel image and the training images, resulting in a warped novel image having an object. Thereafter, the system determines if the object in the warped novel image is anomalous by measuring the distance of the warped novel image from the subspace model. Finally, if anomalous, an operator is notified accordingly.

Abstract: A method of displaying sensed displacement is such as to collect single dimension light distribution data using a single dimensional imaging device; transmit the light distribution data to a processor; and display the light distribution data as a line bright wave form on a display using software implemented by the processor.

Abstract: To suitably reduce data amount. For example, feature points from a branch point or an end point to the next branch point or an end point in a blood vessel line are set as a group. In the three feature points satisfying one of the condition that the absolute value of the outer product of vectors in continuous three feature points is smaller than an outer product threshold value, and the condition that a cosine in the above three feature points is smaller than a cosine threshold value, the middle one of the three feature points satisfying the other of the above conditions and being the smallest is eliminated, for every group.

Abstract: Methods, storage mediums, and systems for image data processing are provided. Embodiments for the methods, storage mediums, and systems include configurations to perform one or more of the following steps: background signal measurement, particle identification using classification dye emission and cluster rejection, inter-image alignment, inter-image particle correlation, fluorescence integration of reporter emission, and image plane normalization.

Abstract: The signature verification methods and devices disclosed herein can be used to verify signatures signed on electronic key pads and other input devices, such as signature pens. Many different aspects of a dynamic signature can be measured in an attempt to verify the signature, including, but not limited to spatial measurements, measurements over time, and frequency. These measurements can be of points on a signature, but they can also be pressure, velocity, and acceleration, to name just a few. These different aspects can then be analyzed using, for example, time series, and spectral similarities. Further, the spectral similarities can be analyzed using wavelet-transforms. In another embodiment, these analysis systems and methods can be applied to written signatures as well as dynamic written signatures.

Abstract: An image processing apparatus includes the following elements. An evaluation information storage section stores a plurality of evaluation information sets for determinations as to whether an image subjected to determination is a target image. An image input section inputs an image. A face detection section detects a face included in the input image. A normalization section normalizes a face image that is an image segment including the detected face so that the face image has a predetermined resolution. A feature extraction section extracts a feature amount of the normalized face image. An attribute information generation section makes a determination on the basis of the extracted feature amount and each evaluation information set as to whether the face image is the target image associated with the evaluation information set, and generating an attribute information block related to the face included in the face image as the result of determination.

Abstract: A method and system for processing image data to identify objects in an image. A gradient vector image is generated from the image, the gradient vector image identifying a gradient magnitude value and a gradient direction for each pixel of the image. Lines are identified in the gradient vector image. It is determined whether the identified lines are perpendicular, whether more than a predetermined number of pixels on each of the lines identified as perpendicular have a gradient magnitude greater than a predetermined threshold, and whether the individual lines which are identified as perpendicular are within a predetermined distance of each other. A portion of the image is identified as an object if the identified lines are perpendicular, more than the predetermined number of pixels on each of the lines have a gradient magnitude greater than the predetermined threshold, and are within a predetermined distance of each other.

Abstract: A method for feature matching in image recognition is provided. First, image scaling may be based on a feature distribution across scale spaces for an image to estimate image size/resolution, where peak(s) in the keypoint distribution at different scales is used to track a dominant image scale and roughly track object sizes. Second, instead of using all detected features in an image for feature matching, keypoints may be pruned based on cluster density and/or the scale level in which the keypoints are detected. Keypoints falling within high-density clusters may be preferred over features falling within lower density clusters for purposes of feature matching. Third, inlier-to-outlier keypoint ratios are increased by spatially constraining keypoints into clusters in order to reduce or avoid geometric consistency checking for the image.

Abstract: A method of detecting potential changed objects in a first image and a second image, where the first and second images at least partially overlap. The method includes obtaining data describing first and second images and detecting sets of objects in images. A common coordinate system for the sets of objects is calculated. Objects in the sets are eliminated based on positions of the objects and objects outside an area of overlap of the images are eliminated. Data indicating the zero or more remaining objects in the sets is output to indicate potential changed objects.

Abstract: Various methods for tracking and recognition with rotation invariant feature descriptors are provided. One example method includes generating an image pyramid of an image frame, detecting a plurality of interest points within the image pyramid, and extracting feature descriptors for each respective interest point. According to some example embodiments, the feature descriptors are rotation invariant. Further, the example method may also include tracking movement by matching the feature descriptors to feature descriptors of a previous frame and performing recognition of an object within the image frame based on the feature descriptors. Related example methods and example apparatuses are also provided.

Abstract: The present invention provides a method for extracting an image texture signal, a method for identifying image and a system for identifying an image. The method for extracting an image texture signal comprises the following steps: extracting a first image signal; employing a first operation procedure to the first image signal to obtain a second image signal; employing a second operation procedure to the second image signal to obtain a third image signal; employing a third operation procedure to the third image signal to obtain a fourth image signal; outputting the fourth image signal. Therefore, the first image signal is transformed to the fourth image signal via the method for extracting an image texture signal.

Abstract: A method of determining change in a state of an object using images of the object, the method including providing a first image and a second image of the object, the first image and the second image being spaced apart in time, performing a plurality of pixel-based change detection algorithms to obtain a plurality of output difference products/images containing change information and pseudo change information, combining the plurality of output difference products to form a hybrid output difference product and thresholding the output difference product to detect changes in the object.

Abstract: The present invention discloses an object-based image search system and method, whereby a user may visually specify query objects for retrieving relevant images without using any image-segmenting software tool. The method of the present invention comprises: specifying target feature points from sample images which are displayed in an image query interface and determining logic relationships of the target feature points; utilizing a feature-point checking program to correlate the target feature points with target objects; utilizing a feature-similarity calculating program to find out the images relevant to the target objects via the image feature parameters stored in a feature database; arranging and presenting the relevant images in sequence.

Abstract: A local feature descriptor for a point in an image is generated over multiple levels of an image scale space. The image is gradually smoothened to obtain a plurality of scale spaces. A point may be identified as the point of interest within a first scale space from the plurality of scale spaces. A plurality of image derivatives is obtained for each of the plurality of scale spaces. A plurality of orientation maps is obtained (from the plurality of image derivatives) for each scale space in the plurality of scale spaces. Each of the plurality of orientation maps is then smoothened (e.g., convolved) to obtain a corresponding plurality of smoothed orientation maps. Therefore, a local feature descriptor for the point may be generated by sparsely sampling a plurality of smoothed orientation maps corresponding to two or more scale spaces from the plurality of scale spaces.

Abstract: Systems, methods and computer-readable storage media are disclosed for accelerating bitmap remoting by extracting patterns from source bitmaps. A server takes a source image, and performs an edge-detection operation on it. From this edge-detected image, connected segments of the image are determined by executing multiple iterations of a small operation upon the image in parallel—for instance, by assigning each non-white pixel a unique value, then assigning each pixel the minimum value among itself and its neighbors until no pixel is assigned a new value in an iteration. Executing these operations in parallel greatly reduces the time required to identify the connected segments. When the segments are identified, they may be cached by the client so that they do not need to be re-sent to the client when re-encountered by the server.

Abstract: The invention provides a technique for accurate detection of objects appearing in the image, such as single fluorescent molecules, cells, microorganisms, nucleotides, DNA strands, or stars in celestial images. The method allows to differentiate between two combined point sources even if they are closer to each other than the optical resolution of the system. The procedure involves computing several coefficients representing decomposition of the intensity data in the basis of Hermit functions. In the case when the objects are distributed randomly and higher yield of accurately detected objects is desired, the method allows for a tenfold increase in such yield.

Abstract: A method of extracting data from a representation of an identifier, such as a fingerprint is provided. The method includes selecting a plurality of features, such as ridge ends or bifurcations, in the representation of an identifier, considering the positions of those features and generating a reference feature, such a s a centre, from the positions of the plurality of features. The method then links one or more of the features to the reference feature and/or links one or more of the features to one or more of the other features in the plurality of features. From the result, the method extracts data including information on one or more of: one or more of the plurality of features; the reference feature; one or more of the links between a feature and the reference feature; one or more of the links between a feature and another feature.

Abstract: A scene matching reference data generation system inputs a set of probe data. The set of the probe data includes captured images sequentially obtained by a plurality of probe cars and the vehicle positions of the probe cars. The system temporarily stores the captured images, evaluates accuracy reliability degrees of the image-capturing positions of the captured images, and assigns the accuracy reliability degrees to the captured images. The system selects, as a plurality of processing target captured images, a plurality of the captured images having accuracy reliability degrees equal to or higher than a first predetermined degree, extracts image feature points from the selected processing target captured images, and generates image feature point data based on the extracted image feature points. The system generates reference data for scene matching by associating the generated image feature point data with a reference image-capturing position corresponding to the generated image feature point data.

Abstract: An image processing apparatus comprises an anchor point information extraction unit configured to decide coordinates of anchor points and attributes of the anchor points based on a plurality of predetermined extraction rules and a sequence of coordinate points that expresses an outline of image data; a tangential direction decision unit configured to decide tangential directions at an anchor point of interest based on the attribute of the anchor point of interest and coordinate points which are located within a predetermined range from the anchor point of interest; a control point coordinate calculation unit configured to calculate control point coordinates based on the tangential directions and the coordinates of the anchor point of interest; and a data output unit configured to output information including the coordinates of the anchor points and the control point coordinates.

Abstract: An image processing apparatus comprises an anchor point candidate information extraction unit configured to decide coordinates of anchor point candidates and attributes of the anchor point candidates based on a plurality of predetermined extraction rules and a sequence of coordinate points that expresses an outline of image data; an anchor point decision unit configured to decide an anchor point candidate to be reduced based on the attributes of the anchor point candidates and priority orders set in advance for the attributes, and configured to decide anchor points by reducing the decided anchor point candidates to be reduced; a control point coordinate decision unit configured to decide control point coordinates based on the anchor points decided by the anchor point decision unit and the sequence of coordinate points; and a data output unit configured to output information including the coordinates of the decided anchor points and the decided control point coordinates.