Master Thesis Info
Title:
Content based image retrieval using the knowledge of texture, color in binary tree structure
Abstract:
Content base image retrieval is an important research field with many applications. This paper presents a new approach for finding similar images to a given query in a generalpurpose image database using content-based image retrieval. Color and Texture are used as basic features to describe images. In addition, a binary tree structure is used to describe higher level features of an image. It has been used to keep information about separate segments of the images. The performance of the proposed system has been compared with the SIMPLIcity system using COREL image database. our experimental results showed that among 10 image categories available in COREL database, our system had a better performance (10% average) in four categories, equal performance in two and lower performance (7% average) for the remaining four categories.
Thesis Presentaion
Sponsored by IRAN Telecommunications Research Center
Related Documents
Mansoori, Z. Jamzad, M. A survey of content based Image retrieval in general applications, on 14th Internal Conference of Computer Society of Iran, Polytechnique University, Tehran, Iran, 2009
Mansoori, Z. Jamzad, M. Content based Image retrieval using the knowledge of color and texture in Binary Tree Structure, on 22nd Canadian IEEE Conference on Electrical and Computer Engineering, St. John’s, NL, Canada, 2009
See Also:
Contains useful information about implementation of regrading CBIR, and also MATLAB codes
Evaluation of Texture feature for Content-Based Image retrieval
Survey of an Image Retrieval System by using Color and Texture knowledge of images