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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.
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.
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.
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 ...
When scaling a vector graphic image, the graphic primitives that make up the image can be scaled using geometric transformations with no loss of image quality. When scaling a raster graphics image, a new image with a higher or lower number of pixels must be generated. In the case of decreasing the pixel number (scaling down), this usually ...
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.
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.
These features share similar properties with neurons in the primary visual cortex that encode basic forms, color, and movement for object detection in primate vision. [13] Key locations are defined as maxima and minima of the result of difference of Gaussians function applied in scale space to a series of smoothed and resampled images. Low ...