Method for retrieving images in DCT domain

Abstract

The invention provides a method for retrieving images in a DCT domain, which is characterized by comprising the steps as follows: determining fuzzy membership functions of dominant color and texture; selecting characteristic blocks of the dominant colors of the images to be retrieved; extracting characteristic of fuzzy histogram of the dominant color in accordance with the fuzzy membership function and characteristic block of the dominant color to obtain eigenvector K of the dominant color; selecting the characteristic block of the texture; extracting the characteristic of the fuzzy histogramof the texture in accordance with the fuzzy membership function and the characteristic block of the texture to obtain eigenvector TK of the texture; integrating the eigenvectors of the dominant colorand the texture to obtain resultant vector Key=[K, TK] used for expressing image retrieval characteristics. The image retrieval characteristics of the images to be retrieved are used as indexes to besubjected to matching and retrieving with the images in image libraries. The method of the invention is simple in characteristics expression, little in amount of calculation and strong in applicability, and can be applied to content-based image retrieval.

Description

technical field [0001] The invention relates to the fields of computer vision and image processing, in particular to an image retrieval method on a DCT (discrete cosine transform) domain. Background technique [0002] Since 1990, people have proposed content-based image retrieval (Content Based Image Retrieval, referred to as CBIR) technology, which automatically extracts the features of image content by computer, such as color, texture, shape, etc., compiles image indexes according to these features, and calculates query The similarity distance between the image and the images in the database, retrieved by similarity matching. [0003] Color information is the most widely used underlying feature in image retrieval. Swain proposed image retrieval based on color features in 1991. The core idea is to count the frequency of various colors in an image in a certain color space, and then A color histogram is used to measure the similarity of the colors of two images. Pass et al....

AI Technical Summary

Problems solved by technology

[0006] The above-mentioned texture feature expression methods are to extract texture features in the spatial domain of the image, and a large number of images are stored in a compressed form, and the method of converting the image from the compressed domain to the spatial domain for feature extraction is very complicated.

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