Local colour image segmentation using singular value decomposition

Abstract

A method was developed to segment images of complex scenes based on color content. The output of an interest operator provides focus toward regions within an image to be sampled for color content. Statistics for each data set sampled are used to cluster and estimate bounded regions within a transformed color space. Each region respectively represents a specific set. Mappings to transformed regions of color space are found using the singular value decomposition. The mean and variance of each color sample in the transformed color space represent characteristic features for their sampled set of points. Color segmentation is accomplished by establishing whether image pixels belong to any subset represented by the characteristic features. This work contributes a method to color-segment targets in images using local color information within an image stream.