Content Based Image Browse & Retrieval And Developing A Test System

Content Based Image Retrieval (CBIR) has been a very active research area since 1990's. The traditional approach of Image Retrieval is based on the technology of Database Management Systems (DBMS), with the cost of heavy burden of manual annotation. The proposed Content Based Image Browse & Retrieval, however, is a new approach based on Computer Vision, Pattern Recognition which perform the computer-centered image retrieval according to the content of images. In this thesis, firstly, we shows CBIR is based on low-level image features, which are the natural way to represent the content of the image, and can be generated automatically, and feature representation and extraction are the basis of Content-based Image Retrieval. Secondly, we show our discussions on the definitions, representation, extraction and matching algorithms of color, texture and shape features. In this way, for color image we focus mainly on two retrieval schemes: an efficient rated a main color to distinguish color image and improving coarseness algorithm, which improve the retrieval efficiency. Finally, the technical implementation of our content-based image browse and retrieval test system, as well as some key components in building such a test system, is also covered in great detail. As a result, since the 1990's, many Image Retrieval systems have been built, both commercial and academic .We select a few representative systems and highlight their distinct characteristics. In this thesis, we also give a detailed picture of our own Image Retrieval system .The whole system architecture is illustrated thoroughly and the exact operating principle is explained accordingly.