Information preserving histogram segmentation of low contrast images using fuzzy measures

Abstract

This paper proposes an improved histogram segmentation technique. In order to preserve the entropy of images with low contrast, the normalisation function has been performed. Qualitative observations made in present study suggest that the loss in entropy of the images may lead to improper histogram segmentation. As per quantitative investigations, based on the simulation results, the proposed method outperforms other contemporary methods in terms of misclassification error (ME), sensitivity (S) and specificity (Sp). The proposed method has been effectively trained and tested over a data set of 80 and 130 images respectively. Statistical consistency of the results is verified using ANOVA test.