Journal
COGNITIVE COMPUTATION
Volume 5, Issue 4, Pages 610-628Publisher
SPRINGER
DOI: 10.1007/s12559-012-9194-8
Keywords
Visual feature; Visual part detector; Shape encoding; Human visual system; Curvature
Funding
- Basic Science Research Program through the National Research Foundation of Korea (NRF)
- Ministry of Education, Science and Technology [2012-0003252]
- DGIST RAMP
- D Program of the Ministry of Education, Science and Technology of Korea [12-BD-0202]
- National Strategic RAMP
- D Program for Industrial Technology, Korea
- Ministry of Education, Science & Technology (MoST), Republic of Korea [12-BD-0202] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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In this paper, we present a new shape encoding method for object recognition. We first introduce a neurophysiologically inspired visual part detector and shape encoder. The optimal form of the visual part detector is a combination of a circular symmetry detector and a corner-like structure detector. A perceptually novel shape descriptor, known as the curvature-orientation descriptor, is then discussed. This descriptor encodes the curvature as well as the dominant orientation. The perceptual shape encoder enhances the performance of feature matching and object recognition taken from standard test images. The results from the repeatability and object recognition tests validate the feasibility of the proposed perceptual feature extraction method.
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