Research On The Key Techniques Of Content-based Image Retrieval

The content-based image retrieval algorithm using integer-to-integer WT is studied in this paper. The integer-to-integer WT has the following advantages: it fits for image processing because its input and output values are all integers; it extracts image features by using multi- resolution analysis; and it decreases the size of dimensions of the image features.In this paper, the basic knowledge on WT, lifting-scheme and integer-to-integer WT is briefly introduced first, and then the color image is analyzed by integer-to-integer WT multi-resolution in order to reduce the dimensions of the image. Since the low pass part of WT preserves the sketch of the image, better results of the index of color images can be obtained by taking the local region energy and F-norm of WT as the color image features Furthermore, WT coefficients are used to analyze the texture image. As the main features of the texture image are present in the details and the high pass of the WT coefficients denotes the details of the image, the character deduced from WT coefficients can be used to retrieve the texture image.The degree of similarity with ratio in image matching algorithms is defined, which is single to calculate, easy to realize and effective to get better retrieval results.This paper also realizes color image retrieval and binary-target indexing algorithms based on moments; proposes a CBER framework model; introduces general criterions for CBIR system; and finally summarizes the future research direction of CBIR.