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A 32-bit CMYK image (the industry standard as of 2005) is made of four 8-bit channels, one for cyan, one for magenta, one for yellow, and one for key color (typically is black). 64-bit storage for CMYK images (16-bit per channel) is not common, since CMYK is usually device-dependent, whereas RGB is the generic standard for device-independent ...
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.
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.
The first alpha version of OpenCV was released to the public at the IEEE Conference on Computer Vision and Pattern Recognition in 2000, and five betas were released between 2001 and 2005. The first 1.0 version was released in 2006. A version 1.1 "pre-release" was released in October 2008. The second major release of the OpenCV was in October 2009.
The image is convolved with Gaussian filters at different scales, and then the difference of successive Gaussian-blurred images are taken. Keypoints are then taken as maxima/minima of the Difference of Gaussians (DoG) that occur at multiple scales. Specifically, a DoG image (,,) is given by
The Bayer arrangement of color filters on the pixel array of an image sensor Profile/cross-section of sensor. A Bayer filter mosaic is a color filter array (CFA) for arranging RGB color filters on a square grid of photosensors.
This method is normally implemented by first picking out a part of a search image to use as a template. Let (,) represent the value of a search image pixel, where (,) represents the coordinates of the pixel in the search image. For simplicity, assume pixel values are scalar, as in a greyscale image.
In image processing, computer vision and related fields, an image moment is a certain particular weighted average of the image pixels' intensities, or a function of such moments, usually chosen to have some attractive property or interpretation. Image moments are useful to describe objects after segmentation.