Digital Image Correlation Search Method Based on Particle Swarm Algorithm

Abstract:

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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:

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 et al., "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:

$35.00

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