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Proceedings Paper

Robot vision via curvature and color features of objects
Author(s): Kyung-Ho Lee; Hee-Sung Kim
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Paper Abstract

A robot has to recognize the environmental objects correctly to behave as an intelligent machine. A new scheme for object recognition was suggested in this paper. Most of objects can be discriminated through the color and shape properties. The object shape was formed by the surface flatness or curvature. The surface curvature or flatness was computed by the gradients of facet functions. The facet functions can be obtained based on the gray level values of the patches in an image. The color space of the image is transformed into HSI from RGB on each patch. Thus the feature vectors of an object image are composed of the curvature and HSI values of patches in the image.

Paper Details

Date Published: 20 February 2006
PDF: 8 pages
Proc. SPIE 6041, ICMIT 2005: Information Systems and Signal Processing, 60412U (20 February 2006); doi: 10.1117/12.664480
Show Author Affiliations
Kyung-Ho Lee, The Univ. of Seoul (South Korea)
Hee-Sung Kim, The Univ. of Seoul (South Korea)


Published in SPIE Proceedings Vol. 6041:
ICMIT 2005: Information Systems and Signal Processing
Yunlong Wei; Kil To Chong; Takayuki Takahashi, Editor(s)

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