A Texture Segmentation Algorithm and Its Application to Target Recognition

Abstract

Image segmentation is an important research direction in pattern recognition and image understanding, but existing texture segmentation algorithms cannot take full advantage of some texture information of texture image, such as the direction, width, density of ridge line, and so on, and can also not effectively carry out the segmentation of various texture image quality. In order to efficiently implement the texture image segmentation, strengthen the amassing of region segmentation, improve the accuracy of segmentation, achieve more accurate target recognition, this paper defines the direction of the texture, calculates the width of ridge line, gives the distance characteristics between textures, and establishes the mathematical model of the texture border, accordingly presents a new texture segmentation algorithm and compares with other texture segmentation algorithms. The simulation results show that the segmentation algorithm has some advantages to texture segmentation, such as has higher segmentation precision, faster segmentation speed, stronger anti-noise capability, less lost information of target, and so on. The segmented regions hardly contain other texture regions and background region. Moreover, this paper extracts the characteristic points and characteristic parameters in various segmented regions for texture image to obtain the characteristic vector, compares the characteristic vector with the standard template vectors, and identifies the type of target in a range of threshold value. Experimental results show that the proposed target recognition approach has higher recognition rate, faster recognition speed, and stronger anti-noise characteristics than the existing target recognition approaches.