| Color Histogram |
Article Index for Color |
Website Links For Color |
Information AboutColor Histogram |
| CATEGORIES ABOUT COLOR HISTOGRAM | |
| computer graphics | |
| computer vision | |
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Color histograms are a flexible construct that can be built from images in various Color Spaces , whether RGB , Rg-chromaticity or any other color space of any dimension. A histogram of an image is produced first by discretising the colors in the image into a number of bins, and counting the number of image pixels in each bin: This provides a far more compact overview of the data in an image than knowing the exact value of every pixel. The color histogram of an image is invariant with translation and rotation about the viewing axis, and varies only slowly with the angle of view. This makes the color histogram particularly suited to recognising an object of unknown position and rotation within a scene. Importantly, translation of an RGB image into the illumination invariant rg-chromaticity space allows the histogram to operate well in varying light levels. The main drawback of histograms is that the representation is solely dependent of the color of the object being studied. There is no way to distinguish a red and white cup from a red and white plate. Put another way, histogram-based algorithms have no concept of a generic 'cup', and a model of our red and white cup is no use when given an otherwise identical blue and white cup. EXTERNAL LINKS |
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