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Entropy-based methods result in algorithms that use the entropy of the foreground and background regions, the cross-entropy between the original and binarized image, etc., [6] Object Attribute-based methods search a measure of similarity between the gray-level and the binarized images, such as fuzzy shape similarity, edge coincidence, etc.,
An example image thresholded using Otsu's algorithm Original image. In computer vision and image processing, Otsu's method, named after Nobuyuki Otsu (大津展之, Ōtsu Nobuyuki), is used to perform automatic image thresholding. [1]
For example, if applied to 8-bit image displayed with 8-bit gray-scale palette it will further reduce color depth (number of unique shades of gray) of the image. Histogram equalization will work the best when applied to images with much higher color depth than palette size, like continuous data or 16-bit gray-scale images.
Here is an example of color channel splitting of a full RGB color image. The column at left shows the isolated color channels in natural colors, while at right there are their grayscale equivalences: Composition of RGB from three grayscale images. The reverse is also possible: to build a full-color image from their separate grayscale channels.
max is the maximum value for color level in the input image within the selected kernel. min is the minimum value for color level in the input image within the selected kernel. [4] Local contrast stretching considers each range of color palate in the image (R, G, and B) separately, providing a set of minimum and maximum values for each color palate.
where , , and are the color-balanced LMS cone tristimulus values; ′, ′, and ′ are the tristimulus values of an object believed to be white in the un-color-balanced image, and ′, ′, and ′ are the tristimulus values of a pixel in the un-color-balanced image. Matrices to convert to LMS space were not specified by von Kries, but can be ...
A visualization of YCbCr color space The CbCr plane at constant luma Y′=0.5 A color image and its Y′, C B and C R components. The Y′ image is essentially a greyscale copy of the main image. YCbCr, Y′CbCr, 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 digital video and ...
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.