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

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.