基于区域色彩纹理特征描述和DPF匹配的图像检索

该文给出了一种彩色图像检索的新方法。在特征描述时,首先划分连通区域,进而求取勒让德色度矩和纹理共生矩阵,获取区域的色彩和纹理特征(Regional Color and Texture,RCT);在相似度匹配时,将动态局部距离函数(Dynamic Partial distance Function,DPF)应用到动态区域匹配中。实验结果显示,该RCT-DPF方法对彩色图像检索是有效的,并且优于纹理共生矩阵、基于色彩连通的图像纹理检索方法和非DPF区域匹配的多特征描述方法。

Image Retrieval Based on Regional Color-Texture Features Description and DPF Matching

A new method for color image retrieval is introduced in this paper. At first, the image is parted into some connected regions. Rational Legendre chromaticity distribution moments and texture co-occurrence matrices are computed to represent the color and texture features (Regional Color Texture: RCT). Then, Dynamic Partial distance Function (DPF) and dynamic regions matching are used to weight RCT features, for short RCT_DPF. Experimental results indicate that this method RCT-DPF has good performance in image retrieval. To compare with Texture Co-occurrence Matrices(TCM), Multi-component Co-occurrence Matrices(MCM) and RCT, RCT-DPF is better precision.