REGRESSION METHODS FOR AUTOMATED COLOR IMAGE CLASSIFICATION AND THRESHOLDING

Regression methods are used to perform automated image thresholding and colour pixel classification. This is done by considering threshold levels and pixel classification labels as pattern attributes. A regression equation that performs a mapping from the J dimensional feature-pattern space to the K dimensional attribute space is derived. The approach is non-parametric and deterministic, hence no assumptions about the statistical properties of the input patterns or images need be made. Initially a known set of input patterns with associated attributes are used to constitute a training set. A mapping function is then determined from the training patterns and used for estimating attribute values from unknown input patterns, such as images.