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CONGXIN LIU, JIE YANG AND HAI HUANG+
Institute of Image Processing and Pattern Recognition
Shanghai Jiao Tong University
Shanghai, 200240 P.R. China
+Department of Computer Science and Engineering
Zhejiang Sci-Tech University
Hangzhou, 310000 P.R. China
SIFT-like representations are considered as being most resistant to common deformations,
although their computational burden is heavy for low-computation applications
such as mobile image retrieval. H. Bay et al. proposed an efficient implementation of
SIFT called SURF. Although this descriptor has been able to represent the nature of some
underlying image patterns, it is not enough to represent more complicated ones. Also, the
proposed high-dimensional alternative to SURF indeed improves the distinctive character
of the descriptor, while it appears to be less robust. In this paper, an enhanced version of
SURF is proposed. Specifically, it consists of two components: the feature representation
for independent intensity changes and the coupling description for these intensity changes.
To this end, phase space is introduced to model the relationships between the intensity
changes and several statistic metrics quantizing these relationships are also proposed to
meet practical demands. The feature matching experiments demonstrate that our method
achieves a favorable performance close to that of SIFT and faster construction-speed. We
also present results showing that the use of the enhanced SURF representation in a mobile
image retrieval application results in a comparable performance to SIFT.
Received January 21, 2010; revised August 17, 2010 & January 11, 2011; accepted January 31, 2011.
Communicated by Tong-Yee Lee.
* This work was supported by the National Nature Science Foundation of China (No. 61075012) and Projects
of International Cooperation between Ministry of Science and Technology (No. 2009DFA12870).