Paper Title:
A Dual-Population GA Based Visual Identification with Model Matching
  Abstract

Aiming at increasing speed of analysis and understanding of image and improving identification accuracy and efficiency, a novel model matching method with imaged object feature is presented, by which the grey value of image information collected from vision sensor is utilized directly and the finished image recognized result is achieved without pre-processing, so it saves the time for identification. In model matching process, a dual populations GA (DPGA) method is used for searching the best matched object, in which one is the global population served for detecting the possible area existing the optimal position, the other is the local population served for searching in the possible area for the optimal position carefully and quickly. The effectiveness of the method has been verified using real image of workpiece with rectangular feature.

  Info
Periodical
Chapter
Chapter 7: Computer Application in Design and Manufacturing (1)
Edited by
Dongye Sun, Wen-Pei Sung and Ran Chen
Pages
3708-3713
DOI
10.4028/www.scientific.net/AMM.121-126.3708
Citation
Y. Li, F. Gao, Y. M. Huang, X. G. Yang, "A Dual-Population GA Based Visual Identification with Model Matching", Applied Mechanics and Materials, Vols. 121-126, pp. 3708-3713, 2012
Online since
October 2011
Export
Price
$32.00
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