WLSD: A perceptual stimulus model based shape descriptor

Jiatong Li, Baojun Zhao, Linbo Tang*, Chenwei Deng, Lu Han, Jinghui Wu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

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 languageEnglish
Pages (from-to)4513-4532
Number of pages20
JournalKSII Transactions on Internet and Information Systems
Volume8
Issue number12
DOIs
Publication statusPublished - 31 Dec 2014

Keywords

  • Feature selection
  • Multi-scale representation
  • Shape descriptor
  • Shape retrieval

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