Method for implementing image color similarity contrast by taper cone coordinate

Abstract

The invention discloses a method for achieving the similar contrast of image colors by using a taper coordinate, which comprises the following steps: 1) a sample image is converted from RGB to HSL; 2) the sample image expressed by HSL color space carries out discretization; 3) an areal coordinate of each subspace is counted according to the HSL color space after the discretization.; the appearance probability of each subspace is counted; 4) the areal coordinate of each subspace is transformed to the taper coordinate; 5) the color characteristics of the sample image extracted according to step1) to step 4) are deposited to a characteristics database; 6) the corresponding color characteristics of the images to be contrasted are exacted according to step 1) to step 4); 7) according to the distance of two images and the definition of the similarity, the similarity is set; the images to be contrasted are compared with the sample images in the characteristics database of the sample images to find out all similar images which are in line with the requirements of the similarity and then the similar images are displayed. The method of the invention can be applied to image retrieval, whichgreatly improves the accuracy of the image retrieval.

Description

Technical field: [0001] The invention relates to the field of image color similarity comparison, in particular to a search and comparison method for building stone color similarity. Background technique: [0002] With the rapid development of the Internet and digital technology, Web image resources are increasingly abundant. According to the 2005 China Internet Network Information Resources Survey Report released by China Internet Network Information Center, my country's Chinese web pages have reached 2.4 billion, with an average of 6.4 embedded in each web page. Image, the number of Chinese web page image files has exceeded 10 billion. Therefore, image search has become a bottleneck problem in the effective utilization of Web image resources. The current Web image search engine mainly uses keyword search, that is, to extract keywords that may be related to the subject of the image from the relevant text of the web page where the image is located, and store them in the Web i...

AI Technical Summary

Problems solved by technology

However, in computer processing, it must be discretized. At the edge of discrete subspaces, small color changes can lead to division into different subspaces, resulting in distortion of image color contrast.

[0005] 2) Can not correctly reflect the similarity between different colors

Existing algorithms cannot handle this type of problem well

[0006] 3) The problem of too long calculation time in large batch image search

Comparing one by one will make these algorithms useless and not accepted by users

[0007] 4) The problem of intelligent user interface

At present, the user interface of the image search engine is relatively simple, and the interaction ability is poor, and some can only provide a description query interface, that is, a keyword question box

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