2077 results about "Texture feature" patented technology

The invention relates to an intelligent and automatic delineation method for a gross tumor volume and organs at risk, which includes the following steps: (1) tumor multi-modal (mode) image reconstruction, de-noising, enhancement, registration, fusion and other preprocessing; (2) automatic extraction of tumor image features: automatically extracting one or more pieces of tumor image group (texture feature spectrum) information from CT, CBCT, MRI, PET and / or ultrasonic multi-modal (mode) tumor medical image data; and (3) intelligently and automatically delineating a gross tumor volume and organs at risk through deep learning, machine learning, artificial intelligence, regional growing, the graph theory (random walk), a geometric level set, and / or a statistical theory method. A gross tumor volume (GTV) and organs at risk (OAR) can be delineated with high precision.

A method and system for analyzing at least one food item on a food plate is disclosed. A plurality of images of the food plate is received by an image capturing device. A description of the at least one food item on the food plate is received by a recognition device. The description is at least one of a voice description and a text description. At least one processor extracts a list of food items from the description; classifies and segments the at least one food item from the list using color and texture features derived from the plurality of images; and estimates the volume of the classified and segmented at least one food item. The processor is also configured to estimate the caloric content of the at least one food item.

A novel method and system is disclosed to realistically simulate the progress or worsening of facial skin features that contribute to the overall look and condition of the skin. The method utilizes two close-up photographs of the face, one is captured with a digital camera in standard white light, and the other is captured with the same camera in UV light. Then, the method processes these images to simulate the progress or worsening of the major skin features: hyperpigmented spots, wrinkles and small texture features. The worsening of these features simulates facial skin aging due to prolonged exposures to sunlight, biological aging or degradation of the skin health. The progress of these features simulates the improvement of facial skin in terms of overall look and healthiness as though the patient has gone through a treatment. Therefore, the present invention discloses a series of methods that are useful in dermatology, cosmetics and computer animations.

A method and apparatus for classifying possibly malignant lesions from sets of DCE-MRI images includes receiving a set of MRI slice images obtained at respectively different times, where each slice image includes voxels representative of at least one region of interest (ROI). The images are processed to determine the boundaries of the ROIs and the voxels within the identified boundaries in corresponding regions of the images from each time period are processed to extract kinetic texture features. The kinetic texture features are then used in a classification process which classifies the ROIs as malignant or benign. The malignant lesions are further classified to separate TN lesions from non-TN lesions.

There are provided systems and methods for obtaining a three-dimensional surface geometric characteristic and / or texture characteristic of an object. A pattern is projected on a surface of said object. A basic 2D image of said object is acquired; a characteristic 2D image of said object is acquired; 2D surface points are extracted from said basic 2D image, from a reflection of said projected pattern on said object; a set of 3D surface points is calculated in a sensor coordinate system using said 2D surface points; and a set of 2D surface geometric / texture characteristics is extracted.

The invention discloses a method for acquiring a range image by stereo matching of multi-aperture photographing based on color segmentation. The method comprises the following steps of: (1) carrying out image correction on all input images; (2) carrying out the color segmentation on a reference image, and extracting an area with consistent color in the reference image; (3) respectively carrying out local window matching on the multiple input images to obtain multiple parallax images; (4) removing mismatched points which are generated during the matching by applying a bilateral matching strategy; (5) synthesizing the multiple parallax images into a parallax image, and filling parallax information of the mismatched points; (6) carrying out post-treatment optimization on the parallax image to obtain a dense parallax image; and (7) converting the parallax image into a range image according to the relationship between parallax and depth. By acquiring range information from multiple viewpoint images and utilizing image information provided by the multiple viewpoint images, the invention can not only solve the problem of mismatching brought by periodic repetitive textural features and shelter and the like in the images, but also can improve matching precision and obtain an accurate range image.

A method for using computer-aided diagnosis (CAD) for digital tomosynthesis mammograms (DTM) including retrieving a DTM image file having a plurality of DTM image slices; applying a three-dimensional gradient field analysis to the DTM image file to detect lesion candidates; identifying a volume of interest and locating its center at a location of high gradient convergence; segmenting the volume of interest by a three dimensional region growing method; extracting one or more three dimensional object characteristics from the object corresponding to the volume of interest, the three dimensional object characteristics being one of a morphological feature, a gray level feature, or a texture feature; and invoking a classifier to determine if the object corresponding to the volume of interest is a breast cancer lesion or normal breast tissue.

A computerized apparatus for automatically generating an artist coordinated image display based upon a user's favorite image or images. A plurality of digital image templates are stored in a computer accessible memory and each have programmed characteristics associated therewith that are designed by an artist. The characteristics of the template can be programmed and stored, including number, location, shape, color, etc, of windows in the digital template. Color and texture characteristics of a body of the template can be selected to resemble, for example, a frame, which will eventually hold the printed images of the template for display. The windows of the template have stored image attribute requirements associated therewith that are designed by the artist are correlated to match image attributes of at least one user selected image that is placed in at least one other of the windows in the template.

The invention discloses a method for locating a vehicle license plate in complex background. The method comprises the following steps: (1). Differentiating a gray scale mean of a fixed-size region and extracting a vehicle body image from a video; (2). preprocessing the vehicle body image such as gradation, gradient information enhancing, binarization and the like; (3). performing mathematical morphology operation on the processed vehicle body image, and performing primary screening by combining structural features of the vehicle license plate to obtain a plurality of candidate vehicle license plate regions; (4). converting the obtained candidate vehicle license plate regions into an HSV color spatial image; (5). adopting a BP neural network to perform color identification on the HSV color spatial candidate vehicle license plate image, and performing color edge detection by computing the mean color distance between two adjacent regions of a certain pixel; (6). judging edge color pair of an edge point, and eliminating the false vehicle license plate edge; and (7). performing final vehicle license plate location by the texture feature of the vehicle license plate. The method is suitable for complex background, and has higher location accuracy rate and higher robustness.

Systems and methods suitable for capable of autonomous crack detection in surfaces by analyzing video of the surface. The systems and methods include the capability to produce a video of the surfaces, the capability to analyze individual frames of the video to obtain surface texture feature data for areas of the surfaces depicted in each of the individual frames, the capability to analyze the surface texture feature data to detect surface texture features in the areas of the surfaces depicted in each of the individual frames, the capability of tracking the motion of the detected surface texture features in the individual frames to produce tracking data, and the capability of using the tracking data to filter non-crack surface texture features from the detected surface texture features in the individual frames.

An automated cosmetic applicator uses wide-angle cameras, a high-resolution camera, and a differential lighting process to capture images of a body. Software analyzes these images to identify large and small features of the subject and to use these features as landmarks to create in computer memory a corresponding map that is highly accurate and data rich with pixel-level data about the subject's color, light value and texture characteristics. The rich images may be used for tracking the device on the skin, for making accurate corrections to skin, for simulating possible cosmetic enhancements and selecting a desired correction, and for use in other applications such as video games and animations.

A method for manufacturing a magnetic disk comprises the steps of depositing NiP (20) on a substrate (22); depositing NiNb (24) on the NiP; and laser texturing the NiNb. "Sombrero" shaped texture features are more easily formed on the substrate / NiP / NiNb structure than a substrate / NiP structure. The disk is completed by depositing an underlayer (e.g. sputtered Cr or NiP), a magnetic layer (e.g. a Co alloy) and a protective overcoat (e.g. by hydrogenated carbon).

The invention relates to a comprehensive multi-feature image retrieval method, including extraction, index and feature matching of image features, the image features include color feature, texture feature and shape feature. The color feature of the images includes: (1) normalizing the feature as 128 multiply 128 pixel; (2) dividing an image into m multiply n nubs; (3) calculating the C' value of each pixel in every nub, selectiing the main C' value, forming a corresponding two-dimensional matrix A by each main C' value. The invention improves traditional local color histogram by improving extraction method of traditional image color features, which greatly improves precision ratio comparing with common image retrieval method based on color. Application of the image retrieval method that combines multi image features of color, texture and shape can improve precision ratio of the method effectively.

An image analysis device includes circuitry that receives one or more input images and detects a plurality of anatomical landmarks on the one or more input images using a pre-determined face model. The circuitry extracts a plurality of geometric and local texture features based on the plurality of anatomical landmarks. The circuitry selects one or more condition-specific features from the plurality of geometric and local texture features. The circuitry classifies the one or more input images into one or more conditions based on the one or more condition-specific features.

An apparatus for the transfer of heat is presented. The apparatus comprises a textured heat transfer surface disposed to promote condensation of a vapor medium to a liquid condensate, the surface comprising a plurality of surface texture features disposed on the heat transfer surface. The plurality of features has a median size, a median spacing, and a median height displacement such that the force exerted by the surface to pin a drop of condensate to the surface is equal to or less than an external force acting to remove the drop from the surface. Also included are heat pumps, systems for power generation, and distillation systems comprising the apparatus.

An automated cosmetic applicator uses wide-angle cameras, a high-resolution camera, and a differential lighting process to capture images of a body. Software analyzes these images to identify large and small features of the subject and to use these features as landmarks to create in computer memory a corresponding map that is highly accurate and data rich with pixel-level data about the subject's color, light value and texture characteristics. The rich images may be used for tracking the device on the skin, for making accurate corrections to skin, for simulating possible cosmetic enhancements and selecting a desired correction, and for use in other applications such as video games and animations.

The invention belongs to the image processing technique field and particularly relates to the license plate identifying technique and further to a license plate locating method under a complex background. Firstly, a license plate original image of RBG format is converted into HSI format to realize the separation between color information and brightness information; then the obtained saturation component chart and brightness component chart are binarized; then pixels of the original image are classified according to the color information of the license plate and a license plate locating template binary image can be obtained according to the classification results and a mathematical morphology computing is adopted to remove noise from the license plate locating template binary image; then a region growing method is adopted to extract each communication zone of the license plate locating template binary image and an inspection to the license plate size is also carried out, and the communication zones passing the size inspection become candidate license plate zones; the Hough transformation is adopted to correct inclined license plates and then license plate vertical texture characteristics are adopted to further inspect each candidate license plate zone so as to remove the fake candidate zones. The adoption of the invention can effectively enhance the universality and the locating accuracy of the system.

A method of biometrics identification includes obtaining an image including a portion of a hand of an individual, analyzing the image to find one or more feature parameters defining different characteristics of the hand, and comparing the feature parameters with reference information in a database. The features parameters including a geometrical features parameter, a palm line features parameter or a palm texture features parameter.

The invention provides an image multifeature extraction and fusion method and the system, comprising the following steps of, extracting color features from an image to be matched, matching color with the target image, making sure the color similarity degree, if the color similarity degree exceeds the given color similarity degree threshold, entering the next step; extracting additional feature from the image to be matched, matching the auxiliary features with the target image, determining the auxiliary feature similarity degree, the auxiliary features comprise at least one of texture feature and shape feature; on the base of color similarity degree and auxiliary features similarity degree, making synthesis judgment and acquiring the synthesis similarity degree between the image to be matched and the target image, or matching the target image with the auxiliary features extracted from the matching zone of the image to be matched. The method and the system of the invention apply a cascade connected way to match from roughness to exactness, and can determine exactly the similarity zone of the target image and the image to be matched. The method and the system of the invention achieve a rapid and highly effective matching effect and save manpower and resources.

A method, system, and computer program product for identifying at least one three-dimensionally extended lesion within a volumetric region encompassing an inner surface, an outer surface, and intervening tissue of a target organ. The method includes: (1) generating a set of voxels representing a total scanned volume from a set of cross-sectional images of the target organ; (2) performing segmentation to extract a set of voxels representing the volumetric region from the set of voxels representing the total scanned volume; (3) detecting a set of candidate lesions based on geometric feature values of each voxel in the set of voxels representing the volumetric region; and (4) selecting the at least one three-dimensionally extended lesion from the set of candidate lesions based on at least one of volumetric, morphologic, and texture feature values of each lesion in the set of candidate lesions.

The invention discloses a multi-character characteristic fused license plate positioning method. The method comprises the following steps of: (1) performing color image graying processing on an original vehicle image, storing as a gray image, and then performing binarization processing on the gray image to obtain a binary image of the vehicle image; (2) extracting a license plate candidate region; (3) removing the candidate region which does not meet a license plate region condition through the color characteristic and texture characteristic of the license plate candidate region to obtain a license plate region; and (4) accurately positioning a license plate, and obtaining upper, lower, left and right boundaries of a character region in the license plate by using the gray skip characteristic of characters of the license plate region. In the method, the character characteristic of the license plate region is fully utilized, the defect that the conventional license plate positioning method more depends on the shape characteristic and edge characteristic of a license plate frame is overcome, extremely high positioning accuracy is also guaranteed under the condition of a blurry license plate frame, and a division result more meets an observation result of human eyes. The method is intuitive, simple and fast and has better instantaneity.

A pull-on wearable article includes a main portion including an outer cover, the main portion defining a front waist region, a rear waist region, and a crotch region extending between and connecting the front and rear waist regions. First and second extendable side panels extend between and connect the main portion front waist region and the main portion rear waist region to form the article in a closed waist configuration, at least a portion of each side panel being extendable between a relaxed state and an extended state. The article defines first and second side regions, each side region including one of the first and second side panels and a transverse region of the main portion bordering the respective side panel. An informational image is disposed in at least the first side region. The article may further include a texture feature formed in an outer surface of the article and positioned proximate to the informational image to form a composite image. Alternatively or additionally, the image includes a cognitively functional graphic.

The invention discloses a remote sensing image variation detection method based on region similarity. The detection method comprises the steps of: selecting tow-sence remote sensing images with different time phases in a monitored region, wherein the image data of the remote sensing images include multispectral data and panchromatic wave band data; carrying out the image preprocessing on the selected remote sensing images; combining all wave bands of the two remote sensing images in two periods after preprocessing into a one-scene image, dividing the one-scene image to establish the one-to-one mapping relationship of targets of the remote sensing images in two periods; establishing the feature set description of each target according to division results; calculating the region similarity between the targets according to the spectrum features of the targets, and carrying out algebraic calculus according to the textual features and NDVI features of the targets; building up a variable region detection criterion by setting a region similarity threshold value and combining the results of the algebraic calculus, and extracting the variable regions of the remote sensing images in two periods. The detection method can effectively eliminate the phenomenon of salt and pepper and improve the extract precision of the remote sensing image variable regions.

The invention discloses a pedestrian re-identification method based on a generative adversarial network image super-resolution technology. The method includes the following steps: utilizing a Laplace pyramid generative adversarial network to generate a group of clear images, utilizing local maximum event expression and a Dense Correspondences algorithm to separately extract HSV color features, texture features and LAB color features of the images, carrying out fusion on the features, utilizing a cross vision quadratic discriminant analysis algorithm to conduct metric learning on the features, utilizing a Manhattan distance to calculate the distance between a probe set and a gallery set, and finally utilizing a multi-shot mode to carry out 1:N and N:N evaluation. A LAPGAN network is utilized to generate high-resolution image, and then a conventional method is utilized to obtain the features of the images and carry out corresponding matching. Deeping learning and the conventional method are combined to solve the problem of low image resolution caused by illumination, angle and other reasons, and an image matching rate is increased.

A method for verifying areas within an image corresponding to monetary banknotes includes: dividing the image into a plurality of verification sections; generating a banknote boundary map having border sections corresponding to boundaries of valid monetary banknotes; generating a texture decision map from the image having texture sections each having texture values within a valid range according to a valid monetary banknote, determining objects in the texture decision map by removing texture sections in the texture decision map corresponding to border sections in the banknote boundary map; calculating a texture property value for objects according to texture feature values for each verification section; calculating shape property values for each object; and further removing texture sections from the texture decision map corresponding to objects that do not have the texture property value within a first predetermined range and the shape property value within a second predetermined range.

An accurate high-speed moving vehicle mark identification method based on video belongs to a calculation processing method adopting image and mode identification technology to realize vehicle detection and vehicle mark identification. The present invention mainly comprises five function modules, namely a video camera control module, a motion detection module, a vehicle snapshot module, a vehicle positioning module and a vehicle identification module. The present invention acquires a real-time video image through a camera system, judges whether a vehicle passes by processing the video image, judges the motion direction of the vehicle according to motion characteristics, segments a picture of the moving vehicle from an image sequence, positions a vehicle mark through vehicle texture features, and performs classification identification to a vehicle head mark or a vehicle back mark by utilizing vehicle mark features before and after. The present invention can solve the vehicle model and vehicle mark identification of high-speed running vehicles, especially the identification of vehicle back marks.

The invention discloses an automatic image annotation method based on semi-supervised learning. The method comprises the steps that a data set is divided into a training data set, an unlabeled data set and a test set; the SIFT feature and the HOG feature of a training sample are extracted to train an LDA_SVM classifier; color and texture features are extracted to train a neural network; unlabeleddata are used to enable two classifiers to label and predict the same unlabeled sample simultaneously; according to the contribution of the classifiers to the unlabeled sample classification accuracy,the classification results of two classifiers are weighted and fused by an adaptive weighted fusion policy, so as to acquire the final prediction label probability vector of the sample; and finally two classifiers are updated by the sample with high confidence and the predictive label thereof until the preset maximum number of iterations is reached. According to the invention, the method can makefull use of the unlabeled sample to excavate the inherent law of the image feature; the number of annotation samples required for the classifier training is effectively reduced; the annotation effectis great.

An apparatus and method for extracting object based on feature matching between segmented regions in images are provided. The apparatus includes an image input unit for receiving a query image including an object and an object extraction target image from which the object included in the query image is to be extracted; an object position determination unit for determining a position of the object in the object extraction target image using pixel based color feature matching; an image segmentation unit for segmenting each of the query image and the object extraction target image into a plurality of regions using image features including color or texture; and an object region determination unit for performing matching between the segmented regions in the query image and the segmented regions in the determined position of the object in the object extraction target image using color or texture features and determining a final object region using similarity in spatial adjacency between matching regions obtained as a result of the matching. Accordingly, an image region of a particular object can be automatically extracted from an object extraction target image. Therefore, the apparatus can be applied to video editors, video authoring tool, object based video encoder, interactive video authoring tool, and the like.

An image retrieval method with improved performance in which a data image similar to a query image is retrieved by appropriately combining color and texture features. The method for retrieving a data image similar to a query image in an image database containing a plurality of data images involves: calculating color and texture distances between a query image and each data image in the image database; weighting the calculated color and texture distances with predetermined weighting factors; calculating a feature distance between the query image and each data image by combining the weighted color and texture distances by considering human visual perception attributes; and determining the data image similar to the query image using the feature distance. According to the image retrieval method, data images similar to a query image can be retrieved based on the human visual perception mechanism by combining both color and texture features extracted from image regions. In particular, the image region based retrieval enables accurate retrieval of more objects and many kinds of information from a single image.