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Gradient vector flow (GVF), a computer vision framework introduced by Chenyang Xu and Jerry L. Prince, [1] [2] is the vector field that is produced by a process that smooths and diffuses an input vector field. It is usually used to create a vector field from images that points to object edges from a distance.
The pixels with the largest gradient values in the direction of the gradient become edge pixels, and edges may be traced in the direction perpendicular to the gradient direction. One example of an edge detection algorithm that uses gradients is the Canny edge detector. Image gradients can also be used for robust feature and texture matching.
Sobel and Feldman presented the idea of an "Isotropic 3 × 3 Image Gradient Operator" at a talk at SAIL in 1968. [1] Technically, it is a discrete differentiation operator , computing an approximation of the gradient of the image intensity function.
Today, there are much better edge detection methods, such as the Canny edge detector based on the search for local directional maxima in the gradient magnitude, or the differential approach based on the search for zero crossings of the differential expression that corresponds to the second-order derivative in the gradient direction (both of ...
2.3 Gradient magnitude thresholding or lower bound cut ... Download QR code; Print/export ... Canny edge detection in Python OpenCV Archived 2014-04-29 at the ...
OpenCV's Cascade Classifiers support LBPs as of version 2. VLFeat , an open source computer vision library in C (with bindings to multiple languages including MATLAB) has an implementation . LBPLibrary is a collection of eleven Local Binary Patterns (LBP) algorithms developed for background subtraction problem.
OpenCV (Open Source ... Advance vision-based commercial applications by making portable, performance-optimized code available for free ... Gradient boosting trees;
The Prewitt operator is used in image processing, particularly within edge detection algorithms. Technically, it is a discrete differentiation operator, computing an approximation of the gradient of the image intensity function.