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Proceedings Paper

Three-dimensional object recognition using hidden Markov models
Author(s): Young Kug Ham; Kil Moo Lee; Rae-Hong Park
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Paper Abstract

We propose an effective segmentation and recognition algorithm for range images. The proposed recognition system based on the hidden Markov model (HMM) and back-propagation (BP) algorithm consists of three parts: segmentation, feature extraction, and object recognition. For object classification using the BP algorithm we use 3D moments, and for surface matching using the HMM we employ 3D features such as surface area, surface type and line lengths. Computer simulation results show that the proposed system can be successfully applied to segmentation and recognition of range images.

Paper Details

Date Published: 21 April 1995
PDF: 10 pages
Proc. SPIE 2501, Visual Communications and Image Processing '95, (21 April 1995); doi: 10.1117/12.206692
Show Author Affiliations
Young Kug Ham, Sogang Univ. (South Korea)
Kil Moo Lee, Sogang Univ. (South Korea)
Rae-Hong Park, Sogang Univ. (South Korea)


Published in SPIE Proceedings Vol. 2501:
Visual Communications and Image Processing '95
Lance T. Wu, Editor(s)

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