The weighted gradient: A color image gradient applied to morphological segmentation

Abstract

This paper proposes a method for color gradient computation applied to morphological segmentation of color images. The weighted gradient (with weights estimated automatically), proposed in this paper, applied in conjunction with the watershed from markers technique, provides excelent segmentation results, according to a subjective visual criterion. The weighted gradient is computed by linear combination of the gradients from each band of an image under the IHS color space model. The weights to each gradient are estimated by a systematic method that computes the similarity between the image to compute the gradient and an ”ideal image”, whose histogram has an uniform distribution. Several experiments were done in order to compare the segmentation results provided by the weighted gradient to the results provided by other color space metrics, also according to a subjective criterion, and such comparison is present in this paper.