| Class / Patent application number | Description | Number of patent applications / Date published |
|---|
| 382192000 | Feature counting | 47 |
| 20080205766 | Sign Authentication System and Sign Authentication Method - To provide a sign authentication system and method for authenticating the originality of an object having a sign such as a seal or a signature or a pattern which can be deemed as a sign, making counterfeit very difficult even if the mechanism of authentication is revealed, obviating the need for being additionally provided with a special device such as an IC chip used for authenticating the originality. A sign authentication system provides reading a sign such as a personal seal impression as color information for each mesh division, extracting feature points from the color information and storing them, and creating a code for authentication from the feature points. The sign is made with an ink containing color material particles smaller than the mesh division. The feature points on the basis of variation of color information caused are extracted when the mesh division is shifted. | 08-28-2008 |
| 20080205767 | Extraction method, extraction apparatus, program, drawing data creation method, and drawing data creation apparatus - The extraction method and apparatus acquire design data that has a hierarchical structure and is converted into raster data corresponding to drawing onto a substrate and extract from the design data a structural element that composes the design data, is repeatedly described in one hierarchical layer, and satisfies at least one of four extraction conditions concerning a size of the structural element, a number of times of repetition of the structural element in a structural element upper than the structural element, a number of lower structural elements composing the structural element, and a depth of the one hierarchical layer in which the structural element exists. | 08-28-2008 |
| 20100296734 | IDENTIFYING AND CLUSTERING BLOBS IN A RASTER IMAGE - An apparatus is disclosed for processing a raster image comprising a plurality of pixels. The apparatus comprises a computer readable medium for storing steps of a computer program, and a computer processor connected to the computer readable medium for executing the steps of the computer program. A plurality of borders of a first blob in the raster image are identified, and a plurality of borders of a second blob in the raster image are identified. The first blob is compared to the second blob, and when the first blob substantially matches the second blob, a first cluster representing both the first blob and the second blob is generated. | 11-25-2010 |
| 20110135203 | FEATURE SELECTION DEVICE - The feature selection device includes a feature extraction unit that extracts M types of features from each of a plurality of original images and each of a plurality of altered images obtained by applying an alteration process to the plurality of original images; and a feature selection unit that handles an original image and an altered image of the original image as identical images and handles altered images of the same original image as identical images, while handles other images as different images, and with use of discrimination capability which is a degree of discriminating different images and robustness which is a degree that a value of a feature does not vary due to the alteration process applied to an image as evaluation criteria, evaluates the M types of features extracted from the respective images, and selects a collection of N types of features, the N types being smaller in number than that of the M types, from the M types of features as features for discriminating images. | 06-09-2011 |
| 20110158538 | IMAGE FEATURE EXTRACTION DEVICE - This image feature extraction device extracts, from an image, an image feature that makes it possible to adjust the balance between identification capability and robustness, which are the scales of the capability of determining identity of images. This image feature extraction device executes hierarchical quantization to calculate quantization indexes of a plurality of hierarchies in accordance with a previously defined hierarchical quantization method for each quantization target region of an image, and outputs a hierarchical quantization index code, which is an encoding allowing unique specification of the quantization indexes of the respective hierarchies of each quantization target region. | 06-30-2011 |
| 20110170783 | EQUIPMENT AND METHOD FOR ANALYZING IMAGE DATA - An analyzing unit has a linear SVM discriminating section and a nonlinear SVM discriminating section and analyzes an image data having an intensity data for numerous wavelengths in each pixel. In the linear SVM discriminating section, the discrimination as to whether the intensity data is an object data or not is performed for every pixel by using an intensity data of the image data as a feature quantity and using the linear SVM, and subsequently in the nonlinear SVM discriminating section, discrimination using the nonlinear SVM is performed only with respect to the pixels discriminated by the linear SVM as their intensity data being object data. Discrimination can be accomplished with higher precision as compared with the case where all pixels are discriminated only with the linear SVM. Also, as compared with the case where the discrimination is conducted only with the nonlinear SVM for all pixels, the discrimination can be accomplished at higher speed. | 07-14-2011 |
| 20120121184 | IMAGE PROCESSING METHOD, IMAGE PROCESSING APPARATUS, AND IMAGE FORMING APPARATUS - The number of pixels in an identified pixel region is counted, a feature point of the pixel region is extracted and the number of the feature points is counted when the number of the pixels counted has been determined to be equal to or higher than a first threshold value, whether the counted number of the feature points is equal to or lower than a second threshold value is determined, features is calculated based on the feature point extracted from the pixel region when the number of the feature points has been determined to be above the second threshold value, and the first threshold value is changed when the number of the feature points has been determined to be equal to or lower than the second threshold value. Image similarity determination process can be stably performed without any degradation in determination accuracy. | 05-17-2012 |
| 20120201463 | Image Analysis Method and Image Analysis Apparatus - An image analysis method includes acquiring an image of an observation region including a plurality of pixels respectively having a plurality of time serially acquired data, setting an analysis region on the image of the observation region, setting a sub analysis region smaller than the analysis region, intermittently moving the sub analysis region in increments of a pixel interval over the entire analysis region, executing correlation analysis using data of pixels in the sub analysis region every time the sub analysis region is moved, so as to estimate at least a molecular number or a diffusion constant of the sub analysis region, and forming a molecular number or diffusion constant image by mapping the molecular numbers or the diffusion constants. | 08-09-2012 |
| 20120230589 | COMPUTER-READABLE STORAGE MEDIUM STORING IMAGE PROCESSING PROGRAM, IMAGE PROCESSING METHOD, AND IMAGE PROCESSING DEVICE - A computer-readable storage medium storing an image processing program that causes a computer to execute a process includes acquiring the same object identification information included in a plurality of image data items by referring to a storage unit that stores each of the image data items, object identification information that identifies an object included in the image data item, and a location information item that identifies a location of the object in the image data item in association with one another; acquiring the location of the object identified by the acquired object identification information in each of the image data items by referring to the storage unit; computing a difference between the acquired location information items; comparing the difference between the location information items with a predetermined location threshold value; and determining whether the image data items are to be in the same group. | 09-13-2012 |
| 20120308141 | INFORMATION PROCESSING APPARATUS AND METHOD OF PROCESSING INFORMATION, STORAGE MEDIUM AND PROGRAM - There is provided an information processing apparatus including a statistical quantity extraction section calculating similarities between all of a group of multiple images of a first identification target and all of a group of multiple images of a second identification target and extracting a statistical quantity for similarity from the similarities and an identification section identifying the first identification target with the second identification target based on the statistical quantity for similarity. The present technology may be applied to a personal computer, for example. | 12-06-2012 |
| 20130044956 | IMAGE PROCESSING APPARATUS AND METHOD - According to one embodiment, an image processing apparatus includes following units. The correlation calculation unit calculates correlations between a first region and predetermined first basis vectors. The distance calculation unit calculates distances between the first region and second regions on a subspace generated by the second basis vectors selected from the first basis vectors. The feature quantity calculation unit calculates a feature quantity based on the correlations. The weight calculation unit calculates weights based on the distances and the feature quantity. The pixel value calculation unit calculates a weighted average of pixel values according to the weights to generate an output pixel value. | 02-21-2013 |
| 20130051677 | METHODS AND APPARATUS TO COUNT PEOPLE IN IMAGES - Methods, articles of manufacture, and apparatus to count people in an image are disclosed. An example method includes capturing an image of a body region in a first frame; and when a second frame different from the first frame includes the image of the body region, incrementing a first count of persons in the second frame. | 02-28-2013 |
| 20130108163 | IMAGE EVALUATION APPARATUS, IMAGE EVALUATION METHOD, AND PROGRAM | 05-02-2013 |
| 20130236103 | PATTERN IDENTIFYING APPARATUS, PATTERN IDENTIFYING METHOD AND PROGRAM - A pattern identifying apparatus comprises: a generating unit to generate, from input data corresponding to an area, accumulated information corresponding to each position in the area; plural storing units to hold the accumulated information for each dimension; a writing unit to write the accumulated information corresponding to each position to one of the plural storing units according to a predetermined rule concerning the corresponding position; a parallel reading unit to read the accumulated information in parallel from the plural storing units; a feature quantity calculating unit to calculate a feature quantity of a local area by using the read accumulated information; and an identifying unit to identify a predetermined pattern by using the plural feature quantities. The number of the storing units allocated to at least one dimension of the area corresponding to the input data and a reading interval of the accumulated information are in a coprime relation. | 09-12-2013 |
| 20130243328 | REGISTRATION DETERMINATION DEVICE, CONTROL METHOD AND CONTROL PROGRAM THEREFOR, AND ELECTRONIC APPARATUS - Whether an obtained candidate face image is registered or not is appropriately determined. A similarity degree calculating unit calculates the degree of similarity between a candidate face image extracted by a face image extracting unit and a registration face image registered in a storage unit. An in-class variance calculating unit calculates an in-class variance of the degree of similarity of the registered person identified by a registered person identifying unit, and an inter-class variance calculating unit calculates an inter-class variance of the degree of similarity of each registered person registered in the storage unit. A variance ratio calculating unit calculates a variance ratio between the inter-class variance and the in-class variance, and on the basis of the calculated variance ratio, a registration determining unit determines whether a target face image is to be registered or not. | 09-19-2013 |
| 20130259380 | METHODS AND APPARATUS TO COUNT PEOPLE IN IMAGES - Methods and apparatus to count people in images are disclosed. An example method includes generating a first fluctuation factor for a first frame by averaging fluctuation values of a random set of pixels of the first frame; generating a second fluctuation factor for a person indication area of the first frame by averaging fluctuation values of pixels of the person indication area; and marking the person indication area as a false positive when the second fluctuation factor is less than or equal to the first fluctuation factor. | 10-03-2013 |
| 20130259381 | METHODS AND APPARATUS TO COUNT PEOPLE IN IMAGES - Methods and apparatus to count people in images are disclosed. An example method includes dividing a frame of image data into a plurality of segments; calculating first fluctuation factors for the respective segments; calculating a second fluctuation factor for the frame; and identifying ones of the segments having a first fluctuation factor greater than the second fluctuation factor as active segments. | 10-03-2013 |
| 20130279808 | COMPLEX-OBJECT DETECTION USING A CASCADE OF CLASSIFIERS - Complex-object detection using a cascade of classifiers for identifying complex-objects parts in an image in which successive classifiers process pixel patches on condition that respective discriminatory features sets of previous classifiers have been identified and selecting additional pixel patches from a query image by on the basis of probability data. | 10-24-2013 |
| 20130294697 | SYSTEMS AND METHODS FOR PROCESSING MOBILE IMAGES TO IDENTIFY AND EXTRACT CONTENT FROM FORMS - Systems and methods for matching a received image with a template image are disclosed herein. Such systems and methods can advantageously enable an image captured by a mobile device (such as a smartphone or digital camera) to be correctly identified by the processing application. In some embodiments, the received image is first resized in one or both dimensions in order to match or approximately match the dimensions of a given template. The received image and template image can then be superimposed. Next, an optimal translative transformation value can be calculated in order to generate a confidence level for the current possible match. After confidence levels for each template are generated and recorded, the template with the highest confidence level can be selected as the best match for the received image. | 11-07-2013 |
| 20130294698 | IMAGE QUALITY ASSESSMENT - Methods and systems for image quality assessment are disclosed. A method includes accessing an image, identifying features of the image, assessing the features and generating subjective scores for the features based upon a mapping of the features to the subjective scores and based on the subjective scores, generating an image quality score. Access is provided to the image quality score. | 11-07-2013 |
| 20130343654 | GENERATING A BINARY DESCRIPTOR REPRESENTING AN IMAGE PATCH - Embodiments described herein provide a system and method for generating a binary descriptor representing an image patch ( | 12-26-2013 |
| 20140023278 | Feature Extraction And Use With A Probability Density Function (PDF) Divergence Metric - An image of real world is processed to identify blocks as candidates to be recognized. Each block is subdivided into sub-blocks, and each sub-block is traversed to obtain counts, in a group for each sub-block. Each count in the group is either of presence of transitions between intensity values of pixels or of absence of transition between intensity values of pixels. Hence, each pixel in a sub-block contributes to at least one of the counts in each group. The counts in a group for a sub-block are normalized, based at least on a total number of pixels in the sub-block. Vector(s) for each sub-block including such normalized counts may be compared with multiple predetermined vectors of corresponding symbols in a set, using any metric of divergence between probability density functions (e.g. Jensen-Shannon divergence metric). Whichever symbol has a predetermined vector that most closely matches the vector(s) is identified and stored. | 01-23-2014 |
| 20140029855 | IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, AND PROGRAM - An image processing apparatus includes a difference area detection unit and a similarity determination unit. The difference area detection unit is configured to detect a difference area of an input image. The similarity determination unit is configured to calculate a feature amount of a difference area image that is an image of the detected difference area and determine a similarity between the calculated feature amount of the difference area image and a feature amount of a template image for erroneous detection, to determine whether the difference area image is erroneously detected or not. | 01-30-2014 |
| 20140056526 | CODELESS QR CODE - A service provider receives, from a user, picture information captured by a user device from a picture mark associated with a product or service of a merchant. It determines a matching picture image by comparing the picture information with picture images in a server, previously registered by the merchant. It also determines, out of attributes previously registered by the merchant, a matching attribute set uniquely associated with the matching picture image. The attributes may be web links, mobile APPs, or any media files that the merchant desires to communicate to users about its products or services. The service provider then communicates to the user the matching attribute set to be loaded on the user device and direct the user to the web links, mobile APPs, or media files that the merchant predetermined. | 02-27-2014 |
| 20140119663 | Approximate Pyramidal Search for Fast Displacement Matching - A method for approximate pyramidal search for displacement matching is provided that includes performing a complete window-based search at a coarsest resolution level in a resolution pyramid to determine a best matching point in a destination image for each point in a source image, wherein a displacement from each point to the best matching point is determined, counting, for each displacement of the determined displacements, a number of points having the displacement, selecting displacements from the determined displacements based on the number of points counted for each displacement and a predetermined threshold, and performing a search at the next finer resolution level in the resolution pyramid to determine a best matching point in the destination image for each point in the source image, wherein the search for a best matching point for each point is limited to the selected displacements and a reduced search window around each displacement. | 05-01-2014 |
| 20140177965 | IMAGE PROCESSING DEVICE, IMAGE PROCESSING METHOD, AND PROGRAM - There is provided an image processing device including a feature point extraction unit that extracts feature points from an input image, a feature amount calculation unit that calculates feature amounts of the feature points, an image processing unit that processes the marker image to transform the feature amounts of non-distinguishing feature points into feature amounts of distinguishing feature points when the feature points extracted from a marker image included in the input image are not distinguishing, and a marker image generation unit that generates a new marker image based on the processing result. | 06-26-2014 |
| 20140270532 | ATTACHED MATTER DETECTOR AND VEHICLE EQUIPMENT CONTROL APPARATUS - An attached matter detector includes a light source configured to irradiate light toward a plate-like transparent member from one surface thereof, an imaging device configured to image reflection light by attached matter on a surface of the plate-like transparent member, a memory configured to previously store flare information obtained by the image device by turning on the light source in a state without having disturbance light and the attached matter on the surface of the plate-like transparent member, and a difference information-obtaining device configured to obtain difference information between a light-up image as an image obtained by the imaging device with the turned-on light source and a light-out image as an image obtained by the imaging device with the turned-off light source, wherein the attached matter on the surface of the plate-like transparent member is detected based on the difference information and the flare information stored in the memory. | 09-18-2014 |
| 20140286576 | IMAGE FEATURE EXTRACTION DEVICE, IMAGE FEATURE EXTRACTION METHOD, AND IMAGE RECOGNITION DEVICE - An image feature extraction device according to an embodiment includes a gradient image calculator generates intensity gradient data with respect to two different directions based on intensity data of image data; and a gradient count unit calculates a covariance matrix for each partial area obtained by dividing the image data based on the intensity gradient data. The image feature extraction device according to the embodiment further includes a feature data output unit calculates two parameters related to a major axis and a minor axis of an ellipse expressed by the covariance matrix, quantizes a range of the logarithms of the parameters for each of the partial area using a predetermined division number, and outputs a feature vector which contains a value only at a dimension corresponding to the quantized range different from the other dimensions. | 09-25-2014 |
| 20140286577 | IMAGE REGISTRATION DEVICE AND OPERATION METHOD OF THE SAME - Provided is an image registration device including a first feature vector magnitude calculating unit calculating magnitudes of feature vectors corresponding to any one first feature point among feature points of a reference image to create a first magnitude value, a second feature vector magnitude calculating unit calculating magnitudes of feature vectors corresponding to any one second feature point among feature points of a target image to create a second magnitude value, a magnitude difference calculating unit receiving the first and second magnitude values and calculating a difference between the received first and second magnitude values to create a third magnitude value, a first threshold value creating unit creating a first threshold value on the basis of the first magnitude value and a magnitude ratio, and a magnitude difference determining unit receiving the third magnitude value and the first threshold value, and determining a magnitude difference. | 09-25-2014 |
| 20140334733 | EFFICIENT IMAGE MATCHING FOR LARGE SETS OF IMAGES - A system and method to detect similarities between images. The system and method allow comparisons between a query image and one or more catalog images in a manner that is resilient to scanning, scaling, rotating, cropping and other distortions of the query image. The system includes an image processing module that determines and/or calculates principle features of a catalog image and constructs a feature vector using one or more of the principle features. The system also includes a matching module that matches a query image to one or more catalog images. The system finds matches based on a distance measure of features present in the query image and features present in the catalog images. | 11-13-2014 |
| 20140376810 | DETECTION APPARATUS, DETECTION METHOD, AND STORAGE MEDIUM - A detection apparatus that detects a feature point of an image, comprising: a conversion unit configured to convert a first image into a second image; a setting unit configured to set a first target number indicating the number of feature points to be detected from the first image and to set a second target number indicating the number of feature points to be detected from the second image based on the first target number and the number of feature points that are detected from the first image; and a processing unit configured to perform processing for detecting a feature point from the first image based on the first target number and processing for detecting a feature point from the second image based on the second target number. | 12-25-2014 |
| 20140376811 | Classifying Images - Methods, and apparatus for performing methods, for classifying an image. Methods include determining a corresponding set of metrics for each region of two or more regions of a pattern of regions of an image, and classifying the image in response to at least the corresponding set of metrics for each of the two or more regions of the pattern of regions. | 12-25-2014 |
| 20150098655 | Method of Defect Image Classification through Integrating Image Analysis and Data Mining - A method for classifying defect images is provided. Defect images are processed through an automatic optical detection. The present invention integrates image analysis and data mining. Defects are found on the images without using human eye. The defects are classified for reducing product defect rate. Thus, the present invention effectively enhances performance on finding and classifying defects with increased consistency, correctness and reliability. | 04-09-2015 |
| 20150131909 | METHOD, APPARATUS AND COMPUTER PROGRAM PRODUCT FOR GENERATING PANORAMA IMAGES - In accordance with an example embodiment a method, apparatus and computer program product are provided. The method comprise assigning weights to at least one first feature and at least one second feature. The at least one first feature may be associated with a first image and the at least one second feature may be associated with a second image. The weights are assigned based on a distance of the at least one first feature and the at least one second feature from a central portion of the corresponding one of the first image and the second image. The method further includes registering the first image and the second image based at least on the assigned weights to determine transforms between the first image and the second image. The first image and the second image may be based on the determined transform. | 05-14-2015 |
| 20150371084 | Method for Estimating a Number of Objects - A method for estimating a number of objects is to be implemented by a processing module, and is utilized to estimate a number of a plurality of objects having elongated shapes based on an image of the objects that contains substantially-circular end faces of the objects. The method includes steps of generating a characteristic image based on the image of the objects, the characteristic image containing a plurality of characteristic patterns which are associated with the end faces of the objects, calculating a number of the characteristic patterns based on the characteristic image, and obtaining an estimated number of the objects based on at least the number of the characteristic patterns thus calculated. | 12-24-2015 |
| 20160104054 | Saliency Map Computation - Saliency map computation is described. In one or more implementations, a base saliency map is generated for an image of a scene. The base saliency map may be generated from intermediate saliency maps computed for boundary regions of the image. Each of the intermediate saliency maps may represent visual saliency of portions of the scene that are captured in the corresponding boundary region. The boundary regions may include, for instance, a top boundary region, a bottom boundary region, a left boundary region, and a right boundary region. Further, the intermediate saliency maps may be combined in such a way that an effect of a foreground object on the saliency map is suppressed. The foreground objects for which the effect is suppressed are those that occupy a majority of one of the boundary regions. | 04-14-2016 |
| 382193000 | Counting intersections of scanning lines with pattern | 2 |
| 20080226176 | IMAGE DISPLAYING METHODS AND SYSTEMS - A reading/writing method for displaying an input image. M data sets of the input image are written into a first memory buffer at a first line scanning path. The M data sets are then read from the first memory buffer at a zig-zag scanning path to serve as a read-out sequence of data sets. The read-out sequence of data sets is written into to a second memory buffer at the zig-zag scanning path. The read-out sequence of data sets is read from the second memory buffer at a second line scanning path to display the input image in a rotating form. | 09-18-2008 |
| 20120134592 | SYSTEM AND METHOD FOR IMAGE REGISTRATION BASED ON VARIABLE REGION OF INTEREST - An image registration system for aligning first and second images. The novel system includes a first system for extracting a region of interest (ROI) from each image and a second system for coarsely aligning the regions of interest. The first system determines the size and location of the ROI based on the number of features contained within the region. The size of the ROI is enlarged until a number of features contained in the ROI is larger than a predetermined lower bound or until the size is greater than a predetermined upper bound. The second system computes a cross-correlation on the regions of interest using a plurality of transforms to find a coarse alignment transform having a highest correlation. The image registration system may also include a third system for performing sub-pixel alignment on the regions of interest. | 05-31-2012 |
| 382194000 | Counting individual pixels or pixel patterns | 9 |
| 20080310729 | IMAGE PROCESSING METHOD, IMAGE PROCESSING APPARATUS, AND IMAGE FORMING APPARATUS - The number of pixels in an identified pixel region is counted, a feature point of the pixel region is extracted and the number of the feature points is counted when the number of the pixels counted has been determined to be equal to or higher than a first threshold value, whether the counted number of the feature points is equal to or lower than a second threshold value is determined, features is calculated based on the feature point extracted from the pixel region when the number of the feature points has been determined to be above the second threshold value, and the first threshold value is changed when the number of the feature points has been determined to be equal to or lower than the second threshold value. Image similarity determination process can be stably performed without any degradation in determination accuracy. | 12-18-2008 |
| 20100158386 | Universal counting and measurement system - A universal counting and measurement system and method. The system and method are not restricted to a specific application, aimed at counting a specific type of object, but are capable of counting objects of a large variety of sizes and shapes. According to certain embodiments, the system and method are also capable of measuring volumes of materials held within a container or piled on a surface. The shape of the containers or the shape of the pile of material are not limited to a certain prescribed architecture. According to certain embodiments, the system is easily adapted to the different applications and can be made ready to work in a short time. The system is also capable of counting accumulating objects or measuring accumulating volumes within one or more containers or piles. | 06-24-2010 |
| 20100226576 | CARD-COUNTING DEVICE - The device makes it possible to count series of products that are not very thick, stacked side by side, in a determined direction in a retention mechanism. The device includes a lighting mechanism producing one or more light beams covering the whole length of the stack, a detection mechanism with photosensitive elements and including an optical device, making it possible to focus light rays reflected by the stack, a processing mechanism receiving signals originating from the detection circuit, extracting light levels from these signals in correlation with a dimension of stack thickness expressed in pixels, and computing the number of products by determining the repetition of a pattern representative of a product in a noise-free signal resulting from a conversion of the signals received. A Fourier transform is respectively applied to correlation and bicorrelation functions of the signal in order to find a periodic pattern representative of a product if necessary to the nearest phase shift. | 09-09-2010 |
| 20100296735 | IMAGE PROCESSING APPARATUS AND IMAGE PROCESSING PROGRAM PRODUCT FOR DISCRIMINATING DOT REGION IN IMAGE - To accurately discriminate a dot region within an image, the image processing apparatus includes first through fourth isolated dot discriminating portions each judging, for each of a plurality of pixels included in the image, whether the pixel corresponds to a center pixel of an isolated dot, an isolated dot size determining portion detecting an isolated dot size, a dot region discriminating portion judging whether a target pixel is included in a dot region based on a position of the pixel judged as being the center pixel of the isolated dot, and a dot region determining portion determining the dot region based on a position of the target pixel judged as being included in the dot region and the detected isolated dot size. | 11-25-2010 |
| 20140212046 | BIT DEPTH REDUCTION TECHNIQUES FOR LOW COMPLEXITY IMAGE PATCH MATCHING - Two different approaches for reducing the bit depth of the image data so as to reduce the computation and hardware requirement of image patch matching, with minimal loss of matching accuracy are described. Patch matching is able to be implemented in many different ways, but generally involves matching one area of an image with another area of the same image or another area of a different image (e.g. another video frame) through the use of a matching cost function. Transforming the image data to lower bit depth, image processing techniques are able to be implemented to minimize the needed memory and other resources for patch-matching. The complexity/performance trade-off of the approaches are also adjustable so that they are able to be applied for applications with different quality requirements and hardware constraints. | 07-31-2014 |
| 20140241634 | CONTOUR DETECTION AND IMAGE CLASSIFICATION - Systems and methods are provided for creating contour images that represent the contour of objects reflected in images, calculating contour histogram descriptors of the contour images, and classifying images based in part on the histogram descriptors of the contour images. For example, a contour image of an image is created. A radial-polar grid having a plurality of radial-polar bins is then positioned on the contour image. A contour histogram descriptor is created to include a number of bins that correspond to the radial-polar bins of the radial-polar grid, where the contents of the bins of the contour histogram descriptor represent the number of pixels of the contour image that are located in the corresponding radial-polar bins of the radial-polar grid. Images are classified at least based in part on comparisons between contour histogram descriptors of the images and contour histogram descriptors of training images. | 08-28-2014 |
| 20150098656 | IMAGE PROCESSING METHOD AND IMAGE PROCESSING DEVICE - The present invention is a method including: correcting difference between a pixel statistical value of a specific layer and a pixel statistical value of a layer that is wider than the specific layer using an edge information of a layer that is wider than the specific layer; correcting the pixel statistical value of the specific layer using post-correction difference and the pixel statistical value of layer that is wider than the specific layer; recorrecting the post-correction pixel statistical value of the specific layer using difference between a pre-correction pixel statistical value of the specific layer and the post-correction pixel statistical value of the specific layer and the edge information of a layer that is wider than the specific layer; and correcting the target pixel by repeating correction and recorrection until the layer reduces its range from the maximum range to the minimum range. | 04-09-2015 |
| 20150117782 | BANDING NOISE DETECTOR FOR DIGITAL IMAGES - A method and apparatus are provided for detecting banding noise in a digital signal representative of an image. The method includes determining, by a banding noise detector, a count of increment steps in pixel values and a count of decrement steps in pixel values along a filter direction in a neighborhood of a current pixel of the image, checking, by the banding noise detector, if the count of increment steps or the count of decrement steps in the neighborhood of a current pixel exceeds a step threshold value, and classifying, by the banding noise detector, the current pixel as being located in the banding noise zone if the count of increment steps or the count of decrement steps does not exceed the step threshold value. | 04-30-2015 |
| 20160148383 | ESTIMATING RAINFALL PRECIPITATION AMOUNTS BY APPLYING COMPUTER VISION IN CAMERAS - A method and system are provided. The method includes storing a set of references images without rain and spanning a plurality of different light conditions. The method further includes capturing, using a camera, an image of a scene with rain. The method also includes selecting a reference image from the set of reference images based on the light condition of the captured image. The method additionally includes performing an arithmetic subtraction image processing operation between the captured image and the reference image to generate a subtraction image. The method further includes estimating an amount of rain in the subtraction image based on previously calibrated values. | 05-26-2016 |
