A novel image retrieval method based on mutual information descriptors

Authors:
Gang Hou;Ke Zhang;Xiaoxue Zhang;Jun Kong;Ming Zhang
Affiliations:
College of Communication Engineering, Jilin University, Changchun, China,College of Humanities & Sciences, Northeast Normal University, Changchun, China;School of Computer Science and Information Technology, Northeast Normal University, Changchun, China;School of Computer Science and Information Technology, Northeast Normal University, Changchun, China;School of Computer Science and Information Technology, Northeast Normal University, Changchun, China;School of Computer Science and Information Technology, Northeast Normal University, Changchun, China,Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jili ...
Venue:
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
Year:
2013

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Abstract

In this paper, we propose a novel image retrieval method based on mutual information descriptors (MIDs). Under the physiological property of human eyes and human visual perception theory, MIDs are extracted to encode the internal correlation relationship among multiple image feature spaces, characterizing image contents with mutual information features based on the low-level image features, such as color, shape etc., then, the mutual information features fusion strategy is used to imitate the information transfer process in nervous system. When using the MIDs proposed to image retrieval, we can get many advantages such as low dimensionality, a certain robustness of geometric distortions and noise, and describing the human visual retrieval mechanism effectively. Experimental results show that MIDs have high indexing and retrieving performance compared with existing methods for content-based image retrieval (CBIR).