Color printing components of the original image. The next step is to invert each of these separations. When a negative image of the red component is produced, the resulting image represents the cyan component of the image. Likewise, negatives are produced of the green and blue components to produce magenta and yellow separations, respectively. This is done because cyan, magenta, and yellow are subtractive primaries which each represent two of the three additive primaries (RGB) after one additive primary has been subtracted from white light. Cyan, magenta, and yellow are the three basic colors used for color reproduction. When these three colors
Color normalization blue channel like histogram equalization. The comprehensive color normalization is shown to increase localization and object classification results in combination with color indexing. It is an iterative algorithm which works in two stages. The first stage is to use the red, green and blue color space with the intensity normalized, to normalize each pixel. The second stage is to normalize each color channel separately, so that the sum of the color components is equal to one third of the number of pixels. The iterations continue until convergence, meaning no additional changes. Formally: Normalize the color image formula_7 which consists of