Novel Method for Real-Time Moiré Image Analysis Combining Two-Dimensional Entropy Theory and Quantum-Behaved Particle Swarm Optimization

DOI

10.2991/eame-15.2015.70How to use a DOI?

Keywords

Moiré pattern; segmentation; binarization; two-dimensional entropy; QPSO

Abstract

This paper proposes an effective method for improving the processing quality and speed of Moiré pattern segmentation. The method involves using quantum-behaved particle swarm optimization(QPSO) based on two-dimensional (2D) entropy theory.First, the beat phenomena generated by grating interference, also called a Moiré pattern fringe, areextracted through FFT filtering. Subsequently, the fringe is segmented by two thresholds with maximized 2D entropy based on a QPSO algorithm. Verifying the experimental results showed that the proposed approach enabled obtaining an improved segmentation quality, fast computing performance, and favorable convergent effects.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - W.J. Chen
AU  - Y.T. Chen
PY  - 2015/07
DA  - 2015/07
TI  - Novel Method for Real-Time Moiré Image Analysis Combining Two-Dimensional Entropy Theory and Quantum-Behaved Particle Swarm Optimization
BT  - Proceedings of the 2015 International Conference on Electrical, Automation and Mechanical Engineering
PB  - Atlantis Press
SP  - 255
EP  - 258
SN  - 2352-5401
UR  - https://doi.org/10.2991/eame-15.2015.70
DO  - 10.2991/eame-15.2015.70
ID  - Chen2015/07
ER  -