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Algorithmically, LIC takes a vector field and noise texture as input, and outputs a texture. The process starts by generating in the domain of the vector field a random gray level image at the desired output resolution. Then, for every pixel in this image, the forward and backward streamline of a fixed arc length is calculated.
Scalable Vector Graphics are well suited to simple geometric images, while photographs do not fare well with vectorization due to their complexity. Note that the special characteristics of vectors allow for greater resolution example images. The other algorithms are standardized to a resolution of 160x160 and 218x80 pixels respectively.
OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly for real-time computer vision. [2] Originally developed by Intel, it was later supported by Willow Garage, then Itseez (which was later acquired by Intel [3]). The library is cross-platform and licensed as free and open-source software under Apache License ...
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.
A free software Asteroids-like video game played on a vector monitor. Vector-based devices, such as the vector CRT and the pen plotter, directly control a drawing mechanism to produce geometric shapes. Since vector display devices can define a line by dealing with just two points (that is, the coordinates of each end of the line), the device ...
YCbCr, Y′CbCr, or Y Pb/Cb Pr/Cr, also written as YC B C R or Y′C B C R, is a family of color spaces used as a part of the color image pipeline in video and digital photography systems. Y′ is the luma component and C B and C R are the blue-difference and red-difference chroma components.
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The hidden layer outputs a vector that holds classification information about the image and is used in the Template Matching algorithm as the features of the image The feature-based approach to template matching relies on the extraction of image features , such as shapes, textures, and colors, that match the target image or frame.