Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/59340
Title: A wavelet approach for partial occluded object recognition
Authors: Lim, K.B. 
Du, T.H.
Hong, G.S. 
Keywords: Corner detection
Object recognition
Partial occlusion
Wavelet
Issue Date: Nov-2006
Source: Lim, K.B.,Du, T.H.,Hong, G.S. (2006-11). A wavelet approach for partial occluded object recognition. Wuhan Ligong Daxue Xuebao/Journal of Wuhan University of Technology 28 (SUPPL. 1) : 32-39. ScholarBank@NUS Repository.
Abstract: A complete 2-D object recognition algorithm applicable for both standalone and partial occluded object is presented. The main contributions in our work are: we developed a scale and partial occlusion invariant boundary partition algorithm and a multiresolution feature extraction algorithm using wavelet. We also implemented a hierarchical matching strategy for feature matching to reduce computational load, but increase matching accuracy. Experiment result shows proposed recognition algorithm is robust to similarity transform and partial occlusion.
Source Title: Wuhan Ligong Daxue Xuebao/Journal of Wuhan University of Technology
URI: http://scholarbank.nus.edu.sg/handle/10635/59340
ISSN: 16714431
Appears in Collections:Staff Publications

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