Patent application number | Description | Published |
20140053038 | Method for Selecting a LDPC Candidate Code - A method for estimating error probability of LDPC codes includes ordering LDPC codes according to features in each code with known error characteristics. The method includes identifying features in each LDPC code having known error characteristics; adding each code to one or more categories based on the existence of such features; and ranking the LDPC codes according to the level of error risk. | 02-20-2014 |
20140053121 | ACCELERATOR FOR A READ-CHANNEL DESIGN AND SIMULATION TOOL - A computer-aided design method for developing, simulating, and testing a read-channel architecture to be implemented in a VLSI circuit. The method uses a coset operating mode and nonzero-syndrome-based decoding to accelerate the simulation of the read-channel's error-rate characteristics corresponding to different parity-check matrices employed in the read-channel's turbo-decoder, such as a low-density parity-check decoder. The acceleration is achieved through recycling some previously generated log-likelihood-ratio values, which enables the method to sometimes bypass certain time-consuming processing steps therein. | 02-20-2014 |
20140193092 | SUPERRESOLUTION IMAGE PROCESSING USING AN INVERTIBLE SPARSE MATRIX - Superresolution image processing that can be applied when two image frames of the same scene are available so that image information from one frame can be used to enhance the image from the other frame. The superresolution image processing uses a sparse matrix generated based on a Markov random field defined over these two image frames. The sparse matrix is inverted and applied to the image data from the image frame that is being enhanced to generate a corresponding enhanced image. | 07-10-2014 |
20150278582 | Image Processor Comprising Face Recognition System with Face Recognition Based on Two-Dimensional Grid Transform - An image processing system comprises an image processor having image processing circuitry and an associated memory. The image processor is configured to implement a face recognition system utilizing the image processing circuitry and the memory, the face recognition system comprising a face recognition module. The face recognition module is configured to identify a region of interest in each of two or more images, to extract a three-dimensional representation of a head from each of the identified regions of interest, to transform the three-dimensional representations of the head into respective two-dimensional grids, to apply temporal smoothing to the two-dimensional grids to obtain a smoothed two-dimensional grid, and to recognize a face based on a comparison of the smoothed two-dimensional grid and one or more face patterns. | 10-01-2015 |
20150278589 | Image Processor with Static Hand Pose Recognition Utilizing Contour Triangulation and Flattening - An image processing system comprises an image processor having image processing circuitry and an associated memory. The image processor is configured to implement a gesture recognition system utilizing the image processing circuitry and the memory. The gesture recognition system implemented by the image processor comprises a static pose recognition module. The static pose recognition module is configured to identify a hand region of interest in at least one image, to determine a contour of the hand region of interest, to triangulate the determined contour, to flatten the triangulated contour, to compute one or more features of the flattened contour, and to recognize a static pose of the hand region of interest based at least in part on the one or more computed features. | 10-01-2015 |
20150286859 | Image Processor Comprising Gesture Recognition System with Object Tracking Based on Calculated Features of Contours for Two or More Objects - An image processing system comprises an image processor having image processing circuitry and an associated memory. The image processor is configured to implement an object tracking module. The object tracking module is configured to obtain one or more images, to extract contours of at least two objects in at least one of the images, to select respective subsets of points of the contours for the at least two objects based at least in part on curvatures of the respective contours, to calculate features of the subsets of points of the contours for the at least two objects, to detect intersection of the at least two objects in a given image, and to track the at least two objects in the given image based at least in part on the calculated features responsive to detecting intersection of the at least two objects in the given image. | 10-08-2015 |
20150302593 | Front-End Architecture for Image Processing - Systems and methods for image processing may perform one or more operations including, but not limited to: receiving raw image data from at least one imaging device; computing at least one image depth distance from the raw image data; computing one or more image validity flags from the raw image data; generating at least one data validity mask from the one or more image validity flags; determining a background imagery estimation from at least one image depth distance; generating at least one foreground mask from the background imagery estimation and the at least one image depth distance; generating at least one region-of-interest mask from the data validity mask and the foreground mask; and generating filtered raw image data from the raw image data and at least one region of interest mask. | 10-22-2015 |
20150310622 | Depth Image Generation Utilizing Pseudoframes Each Comprising Multiple Phase Images - In one embodiment, an image processor is configured to obtain phase images, and to group the phase images into pseudoframes with each of at least a subset of the pseudoframes comprising multiple ones of the phase images and having as a first phase image thereof one of the phase images that is not a first phase image of an associated depth frame. A velocity field is estimated by comparing corresponding phase images in respective ones of the pseudoframes. Phase images of one or more pseudoframes are modified based at least in part on the estimated velocity field, and one or more depth images are generated based at least in part on the modified phase images. By way of example, different groupings of the phase images into pseudoframes may be used for each obtained phase image, allowing depth images to be generated at much higher rates than would otherwise be possible. | 10-29-2015 |