5469 results about "Edge detection" patented technology

In order to enhance accuracy of determination as to whether an object has contacted a screen and to enhance accuracy of calculation of a coordinate position of the object, edges of an imaged image are detected by an edge detection circuit 76, and by using the edges, it is determined by a contact determination circuit 77 whether or not the object has contacted the screen. Moreover, in order to appropriately control sensitivity of optical sensors in response to external light, by a calibration circuit 93, a drive condition of the optical sensors is changed based on output values of the optical sensors, which are varied in response to the external light.

Systems, methods and structures for combining virtual reality and real-time environment by combining captured real-time video data and real-time 3D environment renderings to create a fused, that is, combined environment, including capturing video imagery in RGB or HSV/HSV color coordinate systems and processing it to determine which areas should be made transparent, or have other color modifications made, based on sensed cultural features, electromagnetic spectrum values, and/or sensor line-of-sight, wherein the sensed features can also include electromagnetic radiation characteristics such as color, infra-red, ultra-violet light values, cultural features can include patterns of these characteristics, such as object recognition using edge detection, and whereby the processed image is then overlaid on, and fused into a 3D environment to combine the two data sources into a single scene to thereby create an effect whereby a user can look through predesignated areas or “windows” in the video image to see into a 3D simulated world, and/or see other enhanced or reprocessed features of the captured image.

Certain embodiments of the present invention provide for a system and method for assessing the accuracy of a surgical navigation system. The method may include acquiring an X-ray image that captures a surgical instrument. The method may also include segmenting the surgical instrument in the X-ray image. In an embodiment, the segmenting may be performed using edge detection or pattern recognition. The distance between the predicted location of the surgical instrument tip and the actual location of the surgical instrument tip may be computed. The distance between the predicted location of the surgical instrument tip and the actual location of the surgical instrument tip may be compared with a threshold value. If the distance between the predicted location of the surgical instrument tip and the actual location of the surgical instrument tip is greater than the threshold value, the user may be alerted.

A catadioptric camera having a perspective camera and multiple curved mirrors, images the multiple curved mirrors and uses the epsilon constraint to establish a vertical parallax between points in one mirror and their corresponding reflection in another. An ASIFT transform is applied to all the mirror images to establish a collection of corresponding feature points, and edge detection is applied on mirror images to identify edge pixels. A first edge pixel in a first imaged mirror is selected, its 25 nearest feature points are identified, and a rigid transform is applied to them. The rigid transform is fitted to 25 corresponding feature points in a second imaged mirror. The closes edge pixel to the expected location as determined by the fitted rigid transform is identified, and its distance to the vertical parallax is determined. If the distance is not greater than predefined maximum, then it is deemed correlate to the edge pixel in the first imaged mirror.

The invention provides systems and methods for detection, grading, scoring and tele-screening of cancerous lesions. A complete scheme for automated quantitative analysis and assessment of human and animal tissue images of several types of cancers is presented. Various aspects of the invention are directed to the detection, grading, prediction and staging of prostate cancer on serial sections/slides of prostate core images, or biopsy images. Accordingly, the invention includes a variety of sub-systems, which could be used separately or in conjunction to automatically grade cancerous regions. Each system utilizes a different approach with a different feature set. For instance, in the quantitative analysis, textural-based and morphology-based features may be extracted at image- and (or) object-levels from regions of interest. Additionally, the invention provides sub-systems and methods for accurate detection and mapping of disease in whole slide digitized images by extracting new features through integration of one or more of the above-mentioned classification systems. The invention also addresses the modeling, qualitative analysis and assessment of 3-D histopathology images which assist pathologists in visualization, evaluation and diagnosis of diseased tissue. Moreover, the invention includes systems and methods for the development of a tele-screening system in which the proposed computer-aided diagnosis (CAD) systems. In some embodiments, novel methods for image analysis (including edge detection, color mapping characterization and others) are provided for use prior to feature extraction in the proposed CAD systems.

Embodiments of the present invention relate to methods and systems for detection and delineation of text characters in images which may contain combinations of text and graphical content. Embodiments of the present invention employ intensity contrast edge detection methods and intensity gradient direction determination methods in conjunction with analyses of intensity curve geometry to determine the presence of text and verify text edge identification. These methods may be used to identify text in mixed-content images, to determine text character edges and to achieve other image processing purposes.

An image processing apparatus and a recording medium which can improve the quality of a color document image. Smoothing conditions which are defined by three parameters of “filter size”, “offset”, and “overlap” are set. An edge image which was generated in an edge detection processing is referred to, and a determination is made as to whether an edge pixel exists in a noticed region. When the edge pixel does not exist in the noticed region, a smoothing processing is carried out. When the edge pixel exists in the noticed region, it is determined inappropriate to effect the smoothing processing, and the process goes to a subsequent processing without effecting the smoothing processing. The processing is carried out until the image scanning ends. When the image scanning ends, the next smoothing conditions are set and the processing which is the same as the one described above is performed.

A method for tracking one or multiple objects from an input video sequence allows a user to select one or more regions that contain the object(s) of interest in the first and the last frame of their choice. An initialization component selects the current and the search frame and divides the selected region into equal sized macroblocks. An edge detection component computes the gradient of the current frame for each macroblock and a threshold component decides then which of the macroblocks contain sufficient information for tracking the desired object. A motion estimation component computes for each macroblock in the current frame its position in the search frame. The motion estimation component utilizes a search component that executes a novel search algorithm to find the best match. The mean absolute difference between two macroblocks is used as the matching criterion. The motion estimation component returns the estimated displacement vector for each block. An output component collects the motion vectors of all the predicted blocks and calculates the new position of the object in the next frame.

A method and apparatus for applying gradient edge detection to detect features in a biometric, such as a fingerprint, based on data representing an image of at least a portion of the biometric. The image is modeled as a function of the features. Data representing an image of the biometric is acquired, and features of the biometric are modeled for at least two resolutions. The method and apparatus improves analysis of both high-resolution images of biometrics of friction ridge containing skin that include resolved pores and lower resolution images of biometrics without resolved pores.

An image recognition apparatus operates on data of a color image to obtain an edge image expressing the shapes of objects appearing in the color image, the apparatus including a section for expressing the color attributes of each pixel of the image as a color vector, in the form of a set of coordinates of an orthogonal color space, a section for applying predetermined arrays of numeric values as edge templates to derive for each pixel a number of edge vectors each corresponding to a specific edge direction, with each edge vector obtained as the difference between weighted vector sums of respective sets of color vectors of two sets of pixels which are disposed symmetrically opposing with respect to the corresponding edge direction, and a section for obtaining the maximum modulus of these edge vectors as a value of edge strength for the pixel which is being processed. By comparing the edge strength of a pixel with those of immediately adjacent pixels and with a predetermined threshold value, a decision can be reliably made for each pixel as to whether it is actually located on an edge and, if so, the direction of that edge.

The invention discloses a method for recognizing a road traffic sign for an unmanned vehicle, comprising the following steps of: (1) changing the RGB (Red, Green and Blue) pixel value of an image to strengthen a traffic sign feature color region, and cutting the image by using a threshold; (2) carrying out edge detection and connection on a gray level image to reconstruct an interested region; (3) extracting a labeled graph of the interested region as a shape feature of the interested region, classifying the shape of the region by using a nearest neighbor classification method, and removing a non-traffic sign region; and (4) graying and normalizing the image of the interested region of the traffic sign, carrying out dual-tree complex wavelet transform on the image to form a feature vector of the image, reducing the dimension of the feature vector by using a two-dimension independent component analysis method, and sending the feature vector into a support vector machine of a radial basis function to judge the type of the traffic sign of the interested region. By using the method, various types of traffic signs in a running environment of the unmanned vehicle can be stably and efficiently detected and recognized.

The present application provides an improved segmentation method and system for processing digital images that include an imaged document and surrounding image. A plurality of edge detection techniques are used to determine the edges of the imaged document and then segment the imaged document from the surrounding image.

The invention discloses a regional depth edge detection and binocular stereo matching-based three-dimensional reconstruction method, which is implemented by the following steps: (1) shooting a calibration plate image with a mark point at two proper angles by using two black and white cameras; (2) keeping the shooting angles constant and shooting two images of a shooting target object at the same time by using the same camera; (3) performing the epipolar line rectification of the two images of the target objects according to the nominal data of the camera; (4) searching the neighbor regions of each pixel of the two rectified images for a closed region depth edge and building a supporting window; (5) in the built window, computing a normalized cross-correlation coefficient of supported pixels and acquiring the matching price of a central pixel; (6) acquiring a parallax by using a confidence transmission optimization method having an acceleration updating system; (7) estimating an accurate parallax by a subpixel; and (8) computing the three-dimensional coordinates of an actual object point according to the matching relationship between the nominal data of the camera and the pixel and consequently reconstructing the three-dimensional point cloud of the object and reducing the three-dimensional information of a target.

The invention relates to an autonomously identifying and capturing method of a non-cooperative target of a space robot, comprising the main steps of (1) pose measurement based on stereoscopic vision, (2) autonomous path planning of the target capture of the space robot and (3) coordinative control of a space robot system, and the like. The pose measurement based on the stereoscopic vision is realized by processing images of a left camera and a right camera in real time, and computing the pose of a non-cooperative target star relative to a base and a tail end, wherein the processing comprises smoothing filtering, edge detection, linear extraction, and the like. The autonomous path planning of the target capture of the space robot comprises is realized by planning the motion tracks of joints in real time according to the pose measurement results. The coordinative control of the space robot system is realized by coordinately controlling mechanical arms and the base to realize the optimal control property of the whole system. In the autonomously identifying and capturing method, a self part of a spacecraft is directly used as an identifying and capturing object without installing a marker or a comer reflector on the target star or knowing the geometric dimension of the object, and the planned path can effectively avoid the singular point of dynamics and kinematics.