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.

• Periodical: Applied Mechanics and Materials (Volumes 71-78)
• Pages: 4234-4239
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.71-78.4234
• Online since: July 2011
• Authors: Song Yang, Long Tan Shao, Bo Ya Zhao, Xiao Liu, Gang Lin
• Keywords: Digital Image Correlation (DIC), Displacement, Particle Swarm Optimization Algorithm (PSO), Strain, Sub-Pixel

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