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http://dx.doi.org/10.3837/tiis.2010.06.007

PPD: A Robust Low-computation Local Descriptor for Mobile Image Retrieval  

Liu, Congxin (Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University)
Yang, Jie (Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University)
Feng, Deying (Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.4, no.3, 2010 , pp. 305-323 More about this Journal
Abstract
This paper proposes an efficient and yet powerful local descriptor called phase-space partition based descriptor (PPD). This descriptor is designed for the mobile image matching and retrieval. PPD, which is inspired from SIFT, also encodes the salient aspects of the image gradient in the neighborhood around an interest point. However, without employing SIFT's smoothed gradient orientation histogram, we apply the region based gradient statistics in phase space to the construction of a feature representation, which allows to reduce much computation requirements. The feature matching experiments demonstrate that PPD achieves favorable performance close to that of SIFT and faster building and matching. We also present results showing that the use of PPD descriptors in a mobile image retrieval application results in a comparable performance to SIFT.
Keywords
Local descriptor; image matching; mobile image retrieval; SIFT;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
Times Cited By Web Of Science : 0  (Related Records In Web of Science)
Times Cited By SCOPUS : 0
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