Abstract: Disclosed is an image processing device that includes: a storage unit that holds model information including information indicating a plurality of feature points of a detection object; a correspondence-relationship determination unit that extracts a plurality of feature points included in an input image as a two-dimensional image or a three-dimensional image and that determines a correspondence relationship between an extracted plurality of feature points and a plurality of feature points of the model information; and a position estimating unit that estimates, based on the correspondence relationship, one or a plurality of second positions of the input image corresponding to one or a plurality of first positions set relatively to the detection object. The one or plurality of first positions is included in a point, a line, or a region.

Abstract: An image processing apparatus detecting a plurality of joint positions between a plurality of input images includes a target image generation unit configured to generate a plurality of target images to be searched in a second input image among the input images from a first input image among the input images; a characteristic amount calculation unit configured to calculate a characteristic amount for each of the target images generated by the target image generation unit; and a matching calculation unit configured to calculate a matching between the target image of interest among the target images having the characteristic amounts calculated by the characteristic amount calculation unit, and a part of the second input image, using an evaluation method depending on the characteristic amounts calculated by the characteristic amount calculation unit.

Abstract: An image processing device is provided with an acquiring unit configured to acquire a face image and, a control unit configured to specify a face direction in the face image acquired by the acquiring unit and add, based on the specified face direction, a picture expressing a contour of a face component to the face image.

Abstract: A plurality of processes for emphasizing a stereoscopic effect of an image is supposed and a plurality of stereoscopic effect emphasis processes is integrated in a mode suitable for the image. An image processing device is provided with a stereoscopic effect emphasis processing unit and an integration processing unit. The stereoscopic effect emphasis processing unit executes a plurality of stereoscopic effect emphasis processes on an input image. The integration processing unit integrates results of a plurality of stereoscopic effect emphasis processes according to an integration coefficient used when a plurality of stereoscopic effect emphasis processes is integrated obtained by analyzing the input image. This may be further provided with an image analyzing unit which analyzes the input image to generate the integration coefficient used when a plurality of stereoscopic effect emphasis processes is integrated.

Abstract: A method identifies user demographic characteristics, such as age and gender. First, a plurality of photos are acquired from postings to a social media site by a specific user. A plurality of facial images are identified in the acquired photos. Using a selected subset of the facial images, the method estimates one or more demographic characteristics of the user. In some cases, the estimation uses a profile photograph of the user. In some cases, the facial images are clustered based on similarity. The cluster that most closely matches the profile photo is used for demographic analysis to estimate the characteristics of the user. In some cases, a cluster is selected based on cluster purity, and the images in the cluster are used to estimate the characteristics of the user. In some cases, other self-portrait features are used, such as large facial images or arms along the perimeter of photographs.

Abstract: There is provided an image processing method including acquiring an original image and a disparity map, the disparity map indicating distribution of disparity values associated with respective pixels in the original image, causing a processor to decide a dynamic range of disparity on the basis of the acquired original image and the acquired disparity map, and converting the disparity map in a manner that each disparity in the disparity map is distributed within the decided dynamic range of the disparity.

Abstract: The present invention relates to a method of sensing a fingerprint pattern of a finger using a fingerprint sensing device comprising an array of sensing elements; an electrically conductive finger detecting structure; and finger detecting circuitry connected to the finger detecting structure for providing a finger detection signal indicative of a capacitive coupling between the finger detecting structure and the finger. The method comprises the steps of: comparing the finger detection signal with a first threshold value indicating a first capacitive coupling, and a second threshold value indicating a second capacitive coupling stronger than the first capacitive coupling; and activating at least a subset of the sensing elements when the finger detection signal changes from a first value indicating a capacitive coupling weaker than the first capacitive coupling to a second value indicating a capacitive coupling stronger than the second capacitive coupling.

Abstract: Various methods and systems for dual energy spectral computed tomography imaging are provided. In one embodiment, a method for dual energy imaging comprises generating an image from a higher energy dataset and an updated lower energy dataset, wherein the updated lower energy dataset comprises a combination of a lower energy dataset and a pseudo projection dataset generated from the higher energy dataset. In this way, a weak low energy signal may be recovered, thereby enabling image reconstruction in spite of photon starvation and sparse views.

Abstract: A method of detection of faults on circuit boards comprising the steps of capturing an image (14) of each of a plurality of circuit boards (10) and dividing each of the captured images (14) into a plurality of image segments, each having an image characteristic value. One of the circuit boards 10 is selected for testing and each image segment is compared with corresponding image segments of each other circuit boards (10) to define a plurality of differential image characteristic values. The differential image characteristic values for each image segment are ranked from lowest to highest and an nth differential image characteristic value is selected. An overlay image comprising a representation of the selected differential image characteristic values is created and displayed over the selected circuit board.

Abstract: The invention provides a method for iris based biometric recognition. The method includes receiving an image from an image sensor and determining whether the received image includes an iris. The steps of receiving and determining are repeated until the received image includes an iris. Responsive to determining that a received image includes an iris, iris information corresponding to such received image is compared with stored iris information corresponding to at least one iris and a match decision or a non-match decision is rendered based on an output of the comparison. The invention additionally provides a system and computer program product configured for iris based biometric recognition.

Abstract: An object recognition device includes: a radar that detects objects in the vicinity of a vehicle a camera that detects objects by capturing an image of the vicinity of the vehicle an identical object recognition unit configured to recognize that an object detected by the radar and an object detected by the camera are the same object when the objects are present within a predetermined position range. The identical object recognition unit determines whether the objects are the same object by reducing the predetermined position range when detection using the radar device or the camera is interrupted and then detection is started again.

Abstract: The present invention provides a face recognition method on a computing device, comprising: storing a plurality of training face images, each training face image corresponding to a face class; obtaining one or more face test samples; applying a representation model to represent the face test sample as a combination of the training face images and error terms, wherein a coefficient vector is corresponded to the training face images; estimating the coefficient vector and the error terms by solving a constrained optimization problem; computing a residual error for each face class, the residual error for a face class being an error between the face test sample and the face test sample's representation model represented by the training samples in the face class; classifying the face test sample by selecting the face class that yields the minimal residual error; and presenting the face class of the face test sample.

Abstract: An image processing apparatus according to an embodiment includes an input extraction unit, and a parameter estimation unit. The input extraction unit configured to extract, from time sequence images of medical images obtained by performing a blood perfusion imaging scan on a tissue, a region where a main vessel supplying blood input to the tissue is located as an input part and obtain, based on the input part, a time-density sequence of the blood input as an input time sequence. The parameter estimation unit configured to estimate parameters in a model representing the change of the blood flow at each point in the tissue with the input time sequence, based on the input time sequence, the model and the time sequence images, wherein the parameters include a delay undergone by the blood when flowing from the input part to each point in the tissue.

Abstract: An aspect of the invention includes a system and method for determining a block size and offset for a block artifact. A content is identified. The content can be an image, a frame of video, or any other appropriate content. Edge differences are calculated in each dimension of the content based on the pixel values. The edge differences are filtered. From the filtered edge differences, block attributes, such as block size and offset, can be determined.

Abstract: Systems and methods prevent or restrict the mining of content on a mobile device. For example, a method may include identifying a mining-restriction mark in low order bits or high order bits in a frame buffer of a mobile device and determining whether the mining-restriction mark prevents mining of content. Mining includes non-transient storage of a copy or derivations of data in the frame buffer. The method may also include preventing the mining of data in the frame buffer when the mining-restriction mark prevents mining.

Abstract: Method for the automatic analysis of an image of a biological sample with respect to a pathological relevance, wherein a)local features of the image are aggregated to a global feature of the image using a bag of visual word approach, b) step a) is repeated at least two times using different methods resulting in at least two bag of word feature datasets, c) computation of at least two similarity measures using the bag of word features obtained from a training image dataset and bag of word features from the image, d) the image training dataset comprising a set of visual words, classifier parameters, including kernel weights and bag of word features from the training images, e) the computation of the at least two similarity measures is subject to an adaptive computation of kernel normalization parameters and/or kernel width parameters, f) for each image one score is computed depending on the classifier parameters and kernel weights and the at least two similarity measures, the at least one score being a measure

Abstract: An image processing apparatus comprises a registration unit configured to perform a first registration between a first set of image data and a second set of data, and a second registration between the first set of image data and the second set of data. The apparatus also comprises a registrability determination unit configured to determine a difference between the first registration and the second registration, and to determine a measure of registrability between the first set of image data and the second set of data based on the difference between the first registration and the second registration.

Abstract: A method is disclosed including: receiving raw image data corresponding to a series of raw images; processing the raw image data with an encoder to generate encoded data, where the encoder is characterized by an input/output transformation that substantially mimics the input/output transformation of one or more retinal cells of a vertebrate retina; and applying a first machine vision algorithm to data generated based at least in part on the encoded data.

Abstract: A computer implemented method and apparatus for mitigating face aging errors when performing facial recognition. The method comprises receiving an indication of a face that needs to be searched in an image set, where each image in the image set comprises a timestamp that identifies a creation date of the image, the creation date being in a continuum of successive time intervals; and identifying the indicated face in images taken in each time interval of a plurality of successive time intervals for the indicated face, wherein each face found in images taken in a previous successive time interval is used as a reference set for identifying the face in images taken in a next successive time interval.

Abstract: Image inspecting apparatus compares first image data created as data representing a reference-image acting as an inspecting reference with second image data created as data representing an inspection-image acting as a target to automatically extract a difference point between first and second image data, and includes a storage means for the reference- and inspection-image, an image processing means for establishing correspondences between part of stored reference-image as first image data with part of stored target image as second image data at a pixel level to perform an image matching processing of them, a difference detecting means for comparing image-matched first and second image data to detect a difference between first and second image data, image producing means for comparing difference with a plurality of threshold values to produce error representing image data at each threshold value, and inspecting process using produced error representing image data at each threshold value.