基于復(fù)小波理論多尺度顏色和紋理特征描述的圖像檢索.pdf

1、重慶大學(xué)碩士學(xué)位論文基于復(fù)小波理論多尺度顏色和紋理特征描述的圖像檢索姓名：高延河申請(qǐng)學(xué)位級(jí)別：碩士專業(yè)：計(jì)算機(jī)應(yīng)用技術(shù)指導(dǎo)教師：唐遠(yuǎn)炎2010-04重慶大學(xué)碩士學(xué)位論文 英文摘要 II ABSTRACT As the mass storage facility of computer, multimedia and network technology rapidly developed and widely applied the i

2、mage data increased greatly in the internet. In recent years, the technology that people how to retrieve images that they need from the image database quickly and exactly has become a focus. At the present time in the in

3、ternational, content-based image retrieval(CBIR) technology is one of the resolutions to this challenging question. First of all, the background and importance of the content-based image retrieval were illuminated in thi

4、s part. Then, the situation and hotspot of the CBIR technology today were introduced. At the same time, the native application situation and overseas application situation of content-based image retrieval system were exp

5、lained briefly. In the final of this part, some representative applications of content-based image retrieval system were listed. Secondly, the basic principles of content-based image retrieval system and some key technol

6、ogies like similarity measure were presentation, and then the general framework was discussed in this section. The key factors that decide the efficiency of an image retrieval system are the description of image content

7、and measure the similarity between two images. In the next part of this paper, the complex wavelet theory and its directional characteristics were introduced, here mainly focused on the dual tree complex wavelet transfor

8、mation (DT-CWT), then compared DT-CWT with the traditional wavelet transformation in description of the directions information of image, the description of image characteristics in frequency domain were studied here als

9、o. Some methods discussed here on extraction of color and texture features of images. The retrieval method proposed in this paper will mainly use color auto-correlogram as the color features, and use the information of i

10、mage blocks which can describe texture well as the texture feature, introduced two new operators to describe the texture characteristics, BDIP operator extracted the image edge and valleys information, BVLC operator desc

11、ribe texture roughness. Combination of these two features to represent the characteristics of image at last. Finally, based on the work of above, proposed a method of description and extraction image color and texture fe