Title :
A context-based fusion algorithm for shape retrieval
Author :
El-ghazal, Akrem ; Basir, Otman ; Belkasim, Saeid
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Waterloo, Waterloo, ON
fDate :
June 30 2008-July 3 2008
Abstract :
Shape-based image retrieval has demonstrated encouraging results in retrieving images based on their content. A large body of research in this area has focused on finding effective shape descriptors to search for query images. Nevertheless, the boundless image content variation makes it impossible for a particular choice of descriptor and an algorithm to be effective for all types of images. It is therefore reasonable to approach the problem by combining a group of descriptors and algorithms. Since the effectiveness of an algorithm/descriptor is image dependent, we maintain that for this strategy to achieve its intended goal, the combination scheme must be dynamic as a function of the query context. This paper proposes a context-based fusion algorithm to integrate several shape-based retrieval techniques. Query context is used to determine the most appropriate technique or combination that yields optimal performance. In testing the proposed algorithm, several experiments were conducted.
Keywords :
content-based retrieval; image fusion; image retrieval; learning (artificial intelligence); neural nets; context-based fusion algorithm; image content variation; neural network training; query image search; shape-based image retrieval; Context; co-ranking; fusion; image retrieval; shape;
Conference_Titel :
Information Fusion, 2008 11th International Conference on
Conference_Location :
Cologne
Print_ISBN :
978-3-8007-3092-6
Electronic_ISBN :
978-3-00-024883-2