An Improved K-view-voting Based Texture Classification Method

Texture classification algorithms were employed widely in analyzing remote sensing images, medical images, and industrial images testing and so on. There are many texture classification methods have been developed which including K-Vive based algorithms. Among of them, K-view-voting method achieved best performance by comparing with other K-view based methods. In this paper, after analyzing K-view-voting method, an improved method, which performed in the process of decision, was proposed to improve the classification performance of K-view-voting. To test and evaluate the performance of new method compared with K-view-voting method, several experiments were conducted. The testing images in dataset were selected randomly in a standard database. Experimental results demonstrated the effect of the new method.