Segmenting of the Sonar Image from an Undersea Goal Using Two Dimensional THC Entropy

Abstract Sonar image segmentation is the basis of undersea goal detection and recognition. The THC (Tsallis-Havrda-Charvát) entropy can describe statistical properties non-extensive systems has a wider range applications. There are multiple choices for two features two-dimensional histograms, such as gray value, average value within neighborhood, median mode values so on. This paper investigates results sonar from an using entropies variety gives evaluation indexes results.