Abstract: A method of extracting from a picked-up image an object that is situated in the foreground of a projected backdrop. The method includes an extraction step comprising the steps of establishing a correspondence relationship between pixels of the projected backdrop and of the background of the picked-up image, and defining said object as the set of picked-up pixels that present a departure from said correspondence relationship. The method is applicable to video conferences, to remote teaching, and to television shows.

Abstract: A method for compressing an image includes decomposing the image into one or more regions. A region of the image is selected to be evaluated. The selected region is transformed and quantized if the region does not meet a predetermined compression acceptability criteria. The predetermined compression acceptability criteria may include a specific bit rate, a specific image quality, or combinations thereof. If the region does not meet the predetermined compression acceptability criteria after the region has been transformed and quantized, then the transformation and quantization settings are adjusted and the region is transformed and quantized using the adjusted settings. The region is then encoded when the predetermined compression acceptability criteria has been reached. The encoding may include additional compression stages.

Abstract: In embodiments of spatially coherent nearest neighbor fields, initial matching patches of a nearest neighbor field can be determined at image grid locations of a first digital image and a second digital image. Spatial coherency can be enforced for each matching patch in the second digital image with reference to respective matching patches in the first digital image based on motion data of neighboring matching patches. A multi-resolution iterative process can then update each spatially coherent matching patch based on overlapping grid regions of the matching patches that are evaluated for matching regions of the first and second digital images. An optimal, spatially coherent matching patch can be selected for each of the image grid locations of the first and second digital images based on iterative interaction to enforce the spatial coherency of each matching patch and the multi-resolution iterative process to update each spatially coherent matching patch.

Abstract: An apparatus for delineating a structure of interest includes: a plane selection interface for selecting a contouring plane of selectable orientation in a three-dimensional image or map; a contouring interface for defining a contour in the selected contour plane; and a mesh constructor configured to construct a three-dimensional polygonal mesh delineating the structure of interest in the three-dimensional image or map. The mesh constructor positions constrained vertices on or near a plurality of non-coplanar delineation contours defined using the contouring interface.

Abstract: An image processing apparatus includes a smoothing processing unit which performs smoothing processing, a thinning processing unit which performs thinning processing, an edge direction determination unit which determines an edge direction with respect to each pixel of the image data and a blending processing unit which decides a pixel value of each pixel of when the thinning processing and the smoothing processing are realized at same time. In the image processing apparatus, the blending processing unit decides a pixel value of a target pixel of when the thinning processing and the smoothing processing are realized at the same time depending on a combination of whether the thinning processing is performed or not and whether the smoothing processing is performed or not on the target pixel.

Abstract: An input image is partitioned into a plurality of image regions based on color and color differences. The partitioning comprises assigning a color difference value to plurality of locations within the input image. The partitioning further comprises assigning each of the plurality of locations to an image region of the plurality of image regions, where the assigning occurs according to a particular order. The particular order is based at least in part on color difference values associated with the plurality of locations. The input image may comprise markup. Data representing at least a particular portion of the markup in the input image based on the partitioning is identified. Data representing at least the portion of the markup may be used in a visualization of a customizable product or a manufacturing control associated with a customizable product.

Abstract: The image processing method acquires an input image and information on an image capturing condition, acquires an optical transfer function corresponding to the image capturing condition, calculates a specific frequency at which an index value obtained by using the optical transfer function becomes a predetermined value in each azimuth direction, and produces a window function to divide a frequency band of the input image into lower and higher frequency side bands than the specific frequency in each azimuth direction. Then, the method produces, by using the window function and the optical transfer function, an image restoration filter to perform the image restoration process on the lower frequency side band of the input image and to restrict the image restoration process on the higher frequency side band thereof, and performs the image restoration process using the image restoration filter.

Abstract: Detecting text using stroke width based text detection. As a part of the text detection, a representation of an image is generated that includes pixels that are associated with the stroke widths of components of the image. Connected components of the image are identified by filtering out portions of the pixels using metrics related to stroke width. Text is detected in the image based on the identified connected components.

Abstract: Colors in a color image are transformed by a destination device. The color image comprises pixels with color information. A depth map corresponding to the color image is accessed. The depth map comprises depth information for the color image and indicates the relative position of objects in the color image from a reference point of view. A collection of plural different color transforms is accessed. In addition, a depth value for a target pixel in the color image is determined by using the depth map. There is a selection of a color transform for the target pixel from the collection of plural different color transforms, based on the depth value determined for the target pixel. The selected color transform is applied to the color information of the target pixel by the destination device.

Abstract: A three-dimensional topographical data precision improving device (10) removing noise that occurs in water regions of three-dimensional topographical data comprises a water region specifying unit (13) specifying the range of any one water region; a feature extraction unit (14) extracting feature values within any one water region that describe altitude distribution pattern of each local region in the three-dimensional topographical data; a segmentation unit (15) segmenting the whole range into candidate water regions and non-water regions by comparing the feature values of the specified water region with those of each point in the three-dimensional topographical data; a water region extraction unit (16) extracting water regions from the candidate water regions; and a plane creation unit (17) creating a corrected plane of each water region using the altitudes of the surrounding non-water regions and replacing the water region extracted by the water region extraction unit (16) with the corrected plane.

Abstract: A system and method for identifying characters using a processor and a sparse distributed memory (SDM) module. The system and method are configured to receive image data relating to an object having a surface with physical markings thereon. The physical markings include characters-of-interest. The system and method are also configured to analyze the image data to convert at least one of the characters-of-interest in the image data into a corresponding feature vector. The system and method are also configured to identify the characters-of-interest using the feature vector and the SDM module. A suggested identity for the characters-of-interest is provided.

Abstract: Approaches to segmentation or detection of objects and their boundaries in images (or other data sets) do not rely on machine learning approaches that aim to minimize pixel-level agreement between a computer and a human. Optimizing such pixel-level agreement does not, in general, provide the best possible result if boundary detection is a means to the ultimate goal of image segmentation, rather than an end in itself. In some examples, end-to-end learning of image segmentation specifically targets boundary errors with topological consequences, but otherwise does not require the computer to “slavishly” imitate human placement of boundaries. In some examples, this is accomplished by modifying a standard learning procedure such that human boundary tracings are allowed to change during learning, except at locations critical to preserving topology.

Abstract: A projector includes: a frame image storage unit that stores input image data input to the projector; a block image storage unit that stores a part of the input image data in terms of block image data including N×M (where N and M?2) pixels; a correction processing unit that performs a correction process of correcting a distortion of the image projected onto the projection plane to generate corrected image data which is image data after correction on the basis of the block image data stored in the block image storage unit; and a block image predicting unit that, while the correction processing unit performs the correction process on a predetermined pixel, predicts the block image data necessary for the correction process on a pixel to be processed after the predetermined pixel.

Abstract: When an imaging device receives an image file that includes a color barcode, a processor of the imaging device and/or a remote processor may decode the barcode by identifying informational elements and calibration elements in the barcode. When the calibration elements are detected, one or more color model parameters are determined, and a color model is developed. When an informational element is then detected, a color value is determined for the informational element, the color model is applied using the color model parameters to yield an adjusted color value for the informational element, and the adjusted color value is used to decode the color barcode.

Abstract: A system and method are provided for segmenting an image. The method includes computing an image signature for an input image. One or more similar images are identified from a first set of images, based on the image signature of the input image and image signatures of images in the first set of images. The similar image or images are used to define a cropped region of the input image and a second image signature is computed, this time for the cropped region. One or more similar images are identified from a second set of images, based on the cropped image signature and the image signatures of images in the second set of images. The input image is segmented based on a segmentation map of at least one of the similar images identified in the second set of images.

Abstract: The present invention is directed to an image information decoding apparatus adapted for performing intra-image decoding based on resolution of color components and color space of an input image signal. An intra prediction unit serves to adaptively change block size in generating a prediction image based on a chroma format signal indicating whether resolution of color components is one of 4:2:0 format, 4:2:2 format, and 4:4:4 format, and a color space signal indicating whether color space is one of YCbCr, RGB, and XYZ. An inverse orthogonal transform unit and an inverse quantization unit serve to also change orthogonal transform technique and quantization technique in accordance with the chroma format signal and the color space signal. A decoding unit decodes the chroma format signal and the color space signal to generate a prediction image corresponding to the chroma format signal and the color space signal.

Abstract: The present invention is directed to an image information encoding apparatus adapted for performing intra-image encoding based on resolution of color components and color space of an input image signal. An intra prediction unit serves to adaptively change block size in generating a prediction image based on a chroma format signal indicating whether resolution of color components is one of 4:2:0 format, 4:2:2 format, and 4:4:4 format, and a color space signal indicating whether color space is one of YCbCr, RGB, and XYZ. An inverse orthogonal transform unit and an inverse quantization unit serve to also change orthogonal transform technique and quantization technique in accordance with the chroma format signal and the color space signal. An encoding unit encodes the chroma format signal and the color space signal to generate a prediction image corresponding to the chroma format signal and the color space signal.

Abstract: A system includes a content evaluation device is configured to receive reproduced media content and compare the reproduced media content to reference media content to determine a quality of the reproduced media content relative to the reference media content. The content evaluation device is configured to apply an entropy factor to the determined quality to model human perception of the reproduced media content. A method of determining the entropy factor includes converting the reference media content or the reproduced media content to a grayscale image, counting a number of unique luminance values in the grayscale image, determining the total number of possible luminance values, and defining the entropy factor to be the number of total pixels compared relative to the maximum number of pixels represented by any single luminance value multiplied by the number of possible luminance values.

Abstract: Automated image screening operations of pipelined image processing systems and methods are controlled with a graphical user interface enabling user control of screening analysis process setup and execution and user viewing of results. A gating interface is provided to include and/or exclude cells in an aggregation of individual cell data.

Abstract: A technique that uses repetitive and reliably recognizable parts of handwriting, during digital handwriting data entry, to trigger recognition of digital ink and to repurpose handwriting task area properties. In one example embodiment, this is achieved by drawing one or more delayed strokes of a desired sub-word unit using a stylus on a touch screen. An associated data of the drawn one or more strokes is inputted via the touch screen into a handwriting recognition engine. A first trigger stroke in the drawn one or more strokes that can be used to trigger the sub-word unit recognition by the handwriting recognition engine is then determined. The sub-word unit recognition is then triggered for the drawn one or more strokes based on the determined first trigger stroke by the handwriting recognition engine.