Research Of Image Retrieval Technology Based On Texture Feature

In recent years, a new point appeared in the research of the technology of image retrieval and management. Texture is an important feature in image, used in pathological diagnose, heritage recovery, and so on. This paper mainly researched the technology of image retrieval based on texture feature.Recently, a few image retrieval systems have been realized. But most of them stay at experiment stage, and are used only in special field. It does not receive a wide range of promotion. In this paper, the texture image retrieval algorithms were researched in-depth. It provided valuable support of the theory and frame of reference for content-based image retrieval technology.The main work of this paper included the researches of texture feature extraction algorithms and similarity measurement methods. In the texture feature extraction algorithms, the gray level co-occurrence matrix method was studied, and through experiments, its validity was verified. And then the wavelet transform was studied, through the wavelet decomposition tree to receive the energy value as the image texture feature. Finally, the Tamura texture was analyzed. The experiments verified that this method suited with the human eye's visual experience. In the similarity measurement methods, it studyed Euclidean distance, block distance and the combination distance, and so on, and discussed the relevance feedback algorithm. Finally, this paper gave the distance function.Finally, the four parameters of gray co-occurrence matrix could effectively reflect the image in the direction, interval, changes in the rate and speed information. It not only ensured the accuracy of the feature of the image texture, but also increased the speed of extraction. In the similarity measurement methods, because the weighted block distance considered all features' importance to the image, it improved the accuracy of the image retrieval.