Paper Title:
Digital Image Correlation Search Method Based on Particle Swarm Algorithm
  Abstract

Digital image correlation method is an important optical technique for surface displacement and strain measurement. An approach based on Particle Swarm Optimization algorithm for sub-pixel correlation search is described in this paper. The new Algorithm does not involve reasonable guess of displacement and deformation gradient and the calculation of second-order derivatives of the digital images. Benefiting from the abilities of global optimum and parallelism searching, and compared with genetic algorithm, the new approach can complete the sub-pixel correlation search with high accuracy and less computational consumption. Computer-simulated images are then used to verify this method. The experimental results show that the new approach is a practicable sub-pixel searching method.

  Info
Periodical
Chapter
Chapter 7: Frontiers of Computer Applicated in Building
Edited by
Dongye Sun, Wen-Pei Sung and Ran Chen
Pages
4234-4239
DOI
10.4028/www.scientific.net/AMM.71-78.4234
Citation
S. Yang, L. T. Shao, B. Y. Zhao, X. Liu, G. Lin, "Digital Image Correlation Search Method Based on Particle Swarm Algorithm", Applied Mechanics and Materials, Vols. 71-78, pp. 4234-4239, 2011
Online since
July 2011
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Price
$32.00
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