Abstract: The absolute position of a target object point is determined using a series of images of the scene with overlapping fields of view captured by a camera in positions arranged in at least two dimensions across the scene and position data representing the absolute positions of the camera on capture of the respective images. The images are analyzed to identify sets of image points corresponding to common object points in the scene. A bundle adjustment is performed on the sets of image points that estimates parameters representing the positions of the object points relative to the positions of the camera associated with each image, but without using input orientation data representing the orientation of the camera. The absolute position of the target object point is derived on the basis of the results of the bundle adjustment and the absolute positions of the camera represented by the position data.

Abstract: A computer-implemented method comprises: extracting a setting from a description file of a virtual pan-tilt-zoom (PTZ) camera used to capture an original image through a wide-angle lens; determining a first set of coordinates of a pixel of the original image for each cell of a sparse conversion map represented as a first look-up table, wherein the sparse conversion map corresponds to a sparse grid of pixels of an output image; determining, via interpolating the first set of coordinates, a second set of coordinates of a pixel of the original image for each cell of a full conversion map, wherein the second set of coordinates is represented as a second look-up table, wherein the full conversion map corresponds to a full grid of pixels of the output image; instructing a display to present the output image, wherein the original image is less rectilinear than the output image.

Abstract: The following generally relates to scaling irregularity maps based at least on one of a histogram bin width, an image noise or a contrast agent concentration. A method includes obtaining a non-scaled irregularity map generated based on local weighted histograms of voxel distributions about voxels of interest from volumetric image data of a subject or object. The local weighted histograms include a plurality of bins having a predetermined bin width. The local weights are determined based on a predetermined cluster length. The method further includes scaling the non-scaled irregularity map, generating a scaled irregularity map. The non-scaled irregularity map is scaled based at least on the histogram bin width.

Abstract: A method, system and/or a digital camera provide a geometrical transformation of deformed images of documents comprising text, by text line tracking, resulting in an image comprising parallel text lines. The transformed image is provided as an input to an OCR program either running in a computer system or in a processing element comprised in said digital camera.

Abstract: A method is described that includes capturing a pixelated depth image of a person with a depth camera. The method also includes identifying body parts from the image. The method also includes forming a vector of distances between the body parts. The method also includes comparing the vector against a database of respective body distance vectors for a plurality of people to identify the person.

Abstract: Provided are a computer-aided system (medical device), a computer-aided method, and a computer program product useful in digital templating for prosthetic arthroplasty, for example, total hip arthroplasty. The invention includes digital image capture and scaling features that can be used in conjunction with any digital radiographic image stored using picture archiving and communication system (PACS), regardless of PACS provider or PACS format. Patient radiographic images are captured, imported, and scaled, e.g., to actual size, to match the scale of a digital template of any prosthesis selected by the user. The computer program product is a stand-alone product, used independently of any software interface, including software accessed through connection to a network or the internet. The software, method, and system are suitable for use with a stand-alone computer and permit improved and cost-effective selection of prostheses for any particular clinical situation.

Abstract: A method for analyzing the placenta comprising: selecting one or more placental samples to be analyzed; preparing a histology slide of tissue taken from said placental sample, staining the histology slide using an immunohistochemistry stain, obtaining a digital image of the stained slide; and performing an automated computer analysis on the digital image, wherein the number of trophoblast stromal inclusions is measured.

Abstract: An imaging processing system includes one or more image capturing apparatuses, a reading unit configured to read biometric information from an authentication object person, a similarity calculation unit configured to calculate similarity based on a result of comparing biometric information read by the reading unit with true biometric information of the authentication object person, an authentication unit configured to perform authentication based on a comparison between the similarity calculated by the similarity calculation unit and a preliminarily set threshold, and a control unit configured to control, if the authentication performed by the authentication unit is successful, imaging processing, which is performed by the image capturing apparatus, based on the similarity calculated by the similarity calculation unit.

Abstract: Units which respectively acquire information on an aberration generated by a display optical system and information on an aberration generated by a vision correction optical system used by an observer are arranged. Aberration correction is executed based on the two aberrations. An aberration generated by a combination of the display optical system and the vision correction optical system used by the observer can be appropriately corrected for each observer.

Abstract: Among other things, methods, systems and computer program products are disclosed for managing image files. In one aspect, a method includes displaying, at a data processing device, a preview of images available for import from a storage device, wherein each image is associated with a pair of corresponding image files comprising a compressed image file and a raw image file obtained from a single image capture. At the data processing device, both the raw image file and the compressed image file of the pair associated with at least one of the images are imported. At the data processing device, at least one of the pair of corresponding image files is identified as a master image file for the associated image. At the data processing device, the identified master image file for the associated captured image is displayed.

Abstract: Methods, systems and platforms for digital imaging of multiple regions of an array, and detection and counting of the labeled features thereon, are described.

Abstract: In one embodiment, a system includes a processor to retrieve, from a memory, data of a video frame, the data including measurements of luminance, each of the measurements of luminance being associated with a different entry in a matrix, calculate a weighted average luminance value Ly for the measurements of luminance weighted according to a row position of the one measurement of luminance in the matrix, calculate a weighted average luminance value Lx for the measurements of luminance weighted according to a column position of the one measurement of luminance in the matrix, and create a video signature, S0, of the video frame, the video signature, S0, including the weighted average luminance value Ly and the weighted average luminance value Lx. Related apparatus and methods are also described.

Abstract: A system or method for automatic calculation of scene geometry may include receiving, by a processor, a video stream including a plurality of video frames. A video frame may be divided into blocks, and a vertical vanishing point of the video stream may be determined based on a dominant orientation of detected edges in the blocks. A horizon and scale of the video stream may be estimated based on optical flow of pixels between two consecutive video frames. A set of human heads may be detected in a video frame of the video stream based on the estimated horizon and scale of the video stream.

Abstract: Image processing for productivity applications is provided. An image may be received by a computing device. The computing device may detect the edges comprising the received image and adjust the image based on a skew state of the detected edges. The computing device may then process the adjusted image to correct imbalances. The computing device may then assign an image classification to the processed image. The computing device may then adjust the processed image based on the assigned image classification.

Abstract: A method, an apparatus, an arrangement and a computer readable storage medium for determining an image based at least in part on first data having a first representation is provided. The approach comprises determining a projection of an imaging element on the first representation, the imaging element being arranged to at least partly overlap with the first representation, determining a first subset of data as the subset of the first data corresponding to the projection of the imaging element on the first representation, and determining the image based at least in part on the first subset of data.

Abstract: A system and method directed to receiving a first data set corresponding to patient data at a first time, receiving a second data set corresponding to patient data at a second time, segmenting a first region of interest in the first data set and a second region of interest in the second data set, the first and second regions corresponding to one another and aligning the first region of interest with the second region of interest to highlight a first contour indicating a change in size, shape and orientation between the first and second regions of interest.

Abstract: An image encoder includes an extreme value determiner, a floating point-to-integer converter and an encoder. The extreme value determiner determines minimal and maximal values of a floating point image value of each pixel of a part of an image, an image or a group of images. The floating point-to-integer converter maps the floating point image value of each pixel to an integer image value. The minimal floating point image value is mapped to a minimal integer image value of a predefined range of integer image values and the maximal floating point image value is mapped to a maximal integer image value of the predefined range of integer image values. The encoder encodes the integer image value of each pixel to obtain and provide encoded image data of the part of the image, the image or the group of images.

Abstract: An image processing apparatus and method using a depth image are provided. The image processing apparatus may include a region determination unit to determine a foreground region and a background region in a color image using a depth image, and a color compensation unit to compensate a color with respect to the foreground region and the background region.

Abstract: Methods and systems for recognizing a license plate character. Synthetic license plate character images are generated for a target jurisdiction. A limited set of license plate images can be captured for a target jurisdiction utilizing an image-capturing unit. The license plate images are then segmented into license plate character images for the target jurisdiction. The license plate character images collected for the target jurisdiction can be manually labeled. A domain adaptation technique can be utilized to reduce the divergence between synthetically generated and manually labeled target jurisdiction image sets. Additionally, OCR classifiers are trained utilizing the images after the domain adaptation method has been applied. One or more input license plate character images can then be received from the target jurisdiction. Finally, the trained OCR classifier can be employed to determine the most likely labeling for the character image and a confidence associated with the label.

Abstract: Embodiments of a system and methods for skin detection and pose determination of a hand in an image are generally described herein. A method for may include detecting skin pixels in an image using a multi-layer skin filter and classifying the skin pixels into a set of foreground skin pixels and a set of background skin pixels. The method may include storing information about the set of background skin pixels in a persistent memory. The method may include determining a set of features from the set of foreground skin pixels, and clustering features from the set of features to create a set of hand pose descriptors. The method may include determining a set of candidate hand pose region descriptors and a set of candidate hand pose contour descriptors that match the set of hand pose descriptors and detecting a valid hand pose using the sets of candidate descriptors.