Abstract: A system and method of connectivity-based image processing to identify and extract objects in image data is described. Variations on the method may include iterative local smoothing operations and various algorithmic solutions to improve real-time processing. Variations may also include object extraction processes based on user-provided information about an object in an image.

Abstract: An image processing apparatus includes the following elements. A document-type determining unit determines what type of document a document is on the basis of read information obtained as a result of reading the document by using a document reader. A compression-format setting unit sets, on the basis of the type of document determined by the document-type determining unit, a compression format used for generating image data from the read information. A generator compresses the read information by using the compression format set by the compression-format setting unit so as to generate image data corresponding to the document.

Abstract: An encoding method generates an encoded image according to a predetermined encoding format. The method includes the step of, for each block of pixels, determining an average color of colors of the block of pixels in the predetermined color space; selecting at least one luminance line in dependence on an offset in the color space of the average color from the at least one luminance line; identifying a set of candidate base colors lying on the at least one luminance line; and determining, using the set of candidate base colors and the luminance offset values, the set of encoded pixel colors. The base color and the set of luminance offsets are selected in dependence on an encoding error indicative of a sum distance in the color space between the set of encoded pixel colors and the colors of the block of pixels.

Abstract: Methods, systems and computer-readable storage mediums encoded with computer programs executed by one or more processors for rendering text within an image are disclosed. A block of text is segmented into a plurality of text segments, wherein each text segment comprises a sequence of characters. On each of a plurality of threads running in parallel, a text bitmap is generated for a respective text segment from the plurality of text segments, the text bitmap illustrating the sequence of characters for the respective text segment. Each of the text bitmaps are composited with an image bitmap of a source image, wherein the composited image bitmap comprises a rendering of the block of text onto the source image.

Abstract: An image processing apparatus for region segmentation of an obtained image is provided. The image processing apparatus may include a detecting unit detecting, among plural fundamental regions set to an image, a fundamental region satisfying a predetermined condition as an appropriate region. The image processing apparatus may further include a specifying unit specifying adjacent states of fundamental regions excluding the appropriate region among the plural fundamental regions. The image processing apparatus may also include a region segmentation unit performing region segmentation on each component included in the image based on the adjacent states of the fundamental regions excluding the appropriate region specified by the specifying unit.

Abstract: A method is provided for predicting partitions of at least one group of pixels in an image to be coded, with respect to a group of reference pixels. Accordingly, the group of reference pixels is obtained by calculating a function characteristic of a predetermined mode of prediction, the reference pixels of the group obtained being variable from one partition to another.

Abstract: A system for providing vehicle information at an automobile point of purchase includes a user device having a camera or other image capturing device that is used to capture an image of an automobile. An application on or associated with the image capturing device can either transmit the image to a service provider for processing, or can implement one or more steps in a feature recognition process locally, and thereafter transmit the data to a service provider. In either case, the service provider can then complete the feature recognition processing and identify the automobile from the image. The service provider can then communicate with a make and model database to provide useful information on the vehicle, which can then be transmitted to the user device and conveniently displayed.

Abstract: A position of a pixel serving as an extraction subject is determined by using first image data photographed under a first light source. An extraction range corresponding to the determined position is also determined, by using a color value of the pixel at the determined position and a color value of a pixel at a peripheral position around the determined position in the first image data. A first representative color value is calculated from the first image data and a second representative color value from second image data photographed under a second light source, on the basis of the position of the pixel serving as the extraction subject and the extraction range. A color correction condition for converting a color value depending on the first light source into a color value depending on the second light source is then generated.

Abstract: Implementations of dynamic shape approximation are described. In one technique described herein, a feature of interest in a first coordinate reference system is accessed and at least a portion of the feature is identified and converted to a second coordinate reference system. In one implementation, the size of the portion is chosen such that the portion can be represented in the second coordinate reference system with an acceptable amount of error.

Abstract: Segmentation of certain regions defined on a firearm cartridge case for successful automatic matching of cartridge cases after a cartridge is fired, on the basis of the marks left on the cartridge cases fired. Disclosed is a method for segmentation of a cartridge case base by using surface height matrix information comprising: detecting the center of the cartridge case base; according to this center, obtaining the polar height matrix by subjecting the surface height matrix to polar transformation; acquiring a one-dimensional signal, “Average Height Signal on the Basis of Radius” (AHSBR), by calculation of the mean value on the radius axis applied on the polar height matrix; determining regions similar to circle signal models on the AHSBR and detecting circles; determining the firing pin mark region by threshold processing of the primer region surface height matrix. Letters on the cartridge case base are detected by using slope matrices.

Abstract: The systems and methods described herein relate generally to the detection of retinal abnormalities. More particularly, the systems and methods are used to analyze a fundus or other image of the retina. In some implementations, the image is analyzed by interdependently smoothing and segmenting the image. Using the smoothed and segmented image, retinal features can be identifying in the image. The systems and methods can then analyze the detected retinal features to identify retinal abnormalities.

Abstract: Provided is an apparatus, method and computer-readable medium removing noise of an image. The apparatus may include a channel image correction unit to correct remaining channel images excluding a currently processed channel image, from among a plurality of channel images, using the currently processed channel image, a noise removal unit to remove noise of the currently processed channel image, using the corrected remaining channel images and the currently processed channel image, and a color image reconstruction unit to reconstruct a color image in which noise is removed, by combining the plurality of channel images in which noise is removed when the noise of the plurality of channel images is removed.

Abstract: An image processing method is disclosed that includes dividing image data into a plurality of blocks, determining whether each block is color or monochrome, and compressing the block of image data based on the determination as to whether the block is color or monochrome.

Abstract: A computer implemented method for correcting distortion in an image of a page includes identifying a set of high quality (HQ) words in undistorted regions of one or more images of pages having content related to the content of the page. At least one distorted word in the image the page is identified such that each distorted word corresponds to a high quality word of the set. A global transformation function is generated for application to the image of the page so as to transform the distorted word into its corresponding high quality word. The global transformation function is applied to pixels of the image of the page.

Abstract: A plurality of images are input, specific regions are set for each of the inputted plurality of images, a typical size of the specific regions of each of the plurality of images is determined, and the ratio of the typical size to the size of the entire image is calculated as a typical size ratio. A typical size ratio used as a reference is selected from the typical size ratios calculated for the respective images as a reference ratio, and a candidate region upon trimming that image is determined based on the specific regions of each of the plurality of images. A trimming region for each of the plurality of images is determined based on the reference ratio, and the typical size ratio and candidate region of each image, and each of the plurality of images is trimmed according to the trimming region.

Abstract: A method and apparatus prioritizing video information during coding and decoding. Video information is received and an element of the video information, such as a visual object, video object layer, video object plane or keyregion, is identified. A priority is assigned to the identified element and the video information is encoded into a bitstream, such as a visual bitstream encoded using the MPEG-4 standard, including an indication of the priority of the element. The priority information can then be used when decoding the bitstream to reconstruct the video information.

Abstract: An image processing device comprises a halftoning module, a detecting module, an adding module and a generating module. The halftoning module generates an error diffusion value. The detecting module detects an edge at a current pixel of an image. The adding module adds the pixel value of the current pixel with one of the error diffusion value and an error diffusion seed according to the detecting result. The generating module generates the error diffusion seed. The error diffusion seed is generated by a formula based on the pixel value and location of the current pixel and a random number, or the error diffusion seed is generated by a formula based on the pixel value of the current pixel and a looked-up value, and the looked-up value is retrieved from a look-up table according to the location of the current pixel.

Abstract: A computer implemented method of storing pixel data corresponding to a pixel is disclosed. A first and a second set of pixel data is determined for the pixel. Parity bits for the first set of pixel data are generated, using error correction. An encoded version of the first set of pixel data including the parity bits is stored. An encoded version of the second set of pixel data is stored, using lossless data compression, for use in decoding the first set of pixel data.

Abstract: An image processing apparatus capable of improving image quality, includes a deblocking filter that adjusts a plurality of parameters related to deblocking processing on the basis of activity of an image calculated by an activity calculation section, the total sum of orthogonal transformation coefficients of the image calculated by an orthogonal transformation section, complexity of the image calculated by the rate control unit, or the total sum of prediction errors of the image calculated by a prediction error addition unit.

Abstract: An imaging system containing an electron-multiplying charge-coupled device detector and line-scan spectrograph is used for identifying wholesome and unwholesome freshly slaughtered chicken carcasses on high-speed commercial chicken processing lines. Multispectral imaging algorithms allow for real-time online identification of wholesome and unwholesome chicken carcasses.