Please use this identifier to cite or link to this item: https://doi.org/10.1504/IJCAT.2011.038559
Title: Partially occluded object recognition
Authors: Lim, K.-B. 
Du, T.-H.
Wang, Q.
Keywords: Lipschitz exponent
Object recognition
Partial occlusion
Similarity transformation
Wavelet coefficients
Wavelet descriptor
Issue Date: Feb-2011
Source: Lim, K.-B.,Du, T.-H.,Wang, Q. (2011-02). Partially occluded object recognition. International Journal of Computer Applications in Technology 40 (1-2 SPEC.ISSUE) : 122-131. ScholarBank@NUS Repository. https://doi.org/10.1504/IJCAT.2011.038559
Abstract: Partially occluded object recognition is considered as one of the most difficult problems in machine vision; it has significant importance in industrial environment. In this paper, a 2-D object recognition algorithm applicable for both stand-alone and partially occluded objects is presented. The main contributions are the development of a scale and partial occlusion invariant boundary partition algorithm and a multi-resolution feature extraction algorithm using wavelet. We also implemented a hierarchical matching strategy for feature matching to reduce computational load, but with higher matching accuracy. Experiment results show that the proposed recognition algorithm is robust to similarity transformation and partial occlusion. Copyright © 2011 Inderscience Enterprises Ltd.
Source Title: International Journal of Computer Applications in Technology
URI: http://scholarbank.nus.edu.sg/handle/10635/61048
ISSN: 09528091
DOI: 10.1504/IJCAT.2011.038559
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