Abstract
Motivated by the Weber’s Law, this paper proposes an efficient and robust shape descriptor based on the perceptual stimulus model, called Weber’s Law Shape Descriptor (WLSD). It is based on the theory that human perception of a pattern depends not only on the change of stimulus intensity, but also on the original stimulus intensity. Invariant to scale and rotation is the intrinsic properties of WLSD. As a global shape descriptor, WLSD has far lower computation complexity while is as discriminative as state-of-art shape descriptors. Experimental results demonstrate the strong capability of the proposed method in handling shape retrieval.
Original language | English |
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Pages (from-to) | 4513-4532 |
Number of pages | 20 |
Journal | KSII Transactions on Internet and Information Systems |
Volume | 8 |
Issue number | 12 |
DOIs | |
Publication status | Published - 31 Dec 2014 |
Keywords
- Feature selection
- Multi-scale representation
- Shape descriptor
- Shape retrieval