Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/23763
Title: Chaotic species based particle swarm optimization algorithms and its application in PCB components detection
Authors: Dong, N
Wu, CH
Ip, WH 
Chen, ZQ
Yung, KL 
Keywords: Chaos
Chaotic species based particle swarm optimization
Multi-template matching
Multimodal optimization
Particle swarm optimization
PCB components detection
Issue Date: 2012
Publisher: Pergamon Press
Source: Expert systems with applications, 2012, v. 39, no. 16, p. 12501-12511 How to cite?
Journal: Expert systems with applications 
Abstract: An improved particle swarm optimizer using the notion of chaos and species is proposed for solving a template matching problem which is formulated as a multimodal optimization problem. Template matching is one of the image comparison techniques. This technique is widely applied to determine the existence, location and alignment of a component within a captured image in the printed circuit board (PCB) industry where 100% quality assurance is always required. In this research, an efficient auto detection method using a multiple templates matching technique for PCB components detection is described. The new approach using chaotic species based particle swarm optimization (SPSO) is applied to the multi-template matching (MTM) process. To test its performance, the proposed Chaotic SPSO based MTM algorithm is compared with other approaches by using real captured PCB images. The Chaotic SPSO based MTM method is proven to be superior to other methods in both efficiency and effectiveness.
URI: http://hdl.handle.net/10397/23763
ISSN: 0957-4174
EISSN: 1873-6793
DOI: 10.1016/j.eswa.2012.04.063
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