Histogram Modification for Threshold Selection.
MARYLAND UNIV COLLEGE PARK COMPUTER SCIENCE CENTER
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A standard approach to threshold selection for image segmentation is based on locating valleys in the images gray level histogram. Several methods have been proposed that produce a transformed histogram in which the valley is deeper, or is converted into a peak, and is thus easier to detect. The transformed histograms used in these methods can all be obtained by creating gray level, edge value scatter plots, and computing various weighted projections of these plots on the gray level axis. Using this unified approach makes it easier to understand how the methods work and to predict when a particular method is likely to be effective. The methods are applied to a set of examples involving both real and synthetic images, and the characteristics of the resulting transformed histograms are discussed. Author
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