The Research on Object Recognition from Occluded Images

Hua Li; Qing Min Li; Peng Ying Zhang; Rui Wang

doi:10.4028/www.scientific.net/AMM.182-183.1924

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 182-183The Research on Object Recognition from Occluded...

The Research on Object Recognition from Occluded Images

Abstract:

Based on the contour feature point and genetic algorithm, a m ethod of recogn izing occluded images using feature templet is proposed in this paper. The result computer simulation shows that this method is shift, rotation, and scacle invariant, it obtained satisfactory result when the occluded proportion is less 40%.

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Periodical:

Applied Mechanics and Materials (Volumes 182-183)

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1924-1927

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.182-183.1924

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Online since:

June 2012

Authors:

Hua Li, Qing Min Li, Peng Ying Zhang, Rui Wang

Keywords:

Contour Feature Point, Genetic Algorithm (GA), Object Recognition, Occluded Images

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References

[1] Krolupper F. Recognition of Occluded Objects Using Curvature. Proc of the 12th International Conference in Central Europe on Computer Graphics, Visualization and Compuer Vision. Plzen-Bory, Czech Republic, 2004: 89-92.

Google Scholar

[2] Tiehua D u, Kah B in L im, Geok Soon Hong, et al. 22D occluded object recognition using wavelets [ C ]. Fourth International Conference on Computer and Information Technology (CIT'04) , 2004, 227-232.

DOI: 10.1109/cit.2004.1357201

Google Scholar

[3] Gan Jun ying, Zhang You wei. Face recognition based on moment invariants and neural networks [ J ]. Computer Engineering and Applications, 2002, 38 (7) : 53-56.

Google Scholar

[4] Tsang PWM, Yuen P C, Lam F K Classification of partially occluded objects using 3-point matching and distance transformation[ J ]. Pattern Recognition, 1994, 27 (1) : 27-40.

DOI: 10.1016/0031-3203(94)90015-9

Google Scholar

[5] Balslev IVAR. Noise tolerance of moment invariants in pattern recognition [ J ]. Pattern Recognition Letters, 1998, 19 ( 13 ) : 1183-1189.

DOI: 10.1016/s0167-8655(98)00106-8

Google Scholar

[6] Cho Huak TEH, Roland T CH IN. On image analysis by the methods of moments [ J ]. IEEE Trans on PAM I, 1988, 10 ( 4 ) : 496-513.

Google Scholar

[7] Thomas M B. Finding lines under bounded error[ J ]. Pattern Recognition, 1994, 29 (1) : 1461.

Google Scholar

[8] CAO Li Hua; LIU Wei; and LI Guo Hui. Research and implementation of an image retrieval algorithm based on multiple dominant colors [j]. Journal of computer research and development, 1999. 36(1): 96~100.

Google Scholar