Search

A belly reconstruction and measurement scheme is conducted on a shape-flexible mannequin with digital image correlation technique. We adopted an integer subpixel image matching process. First, a compound feature including Gaussian combined moment and parameters extracted from gray-level co-occurrence matrix is proposed to track an integer pixel between reference and target deformed images. Second, a mutual learning cooperative particle swarm optimization algorithm is employed to locate the subpixel precisely. Each subpopulation does its own optimization independently. The subpopulations keep information communication and knowledge sharing for co-operative evolution to enhance global searching capability. In addition, the previous optimal information from the former interest point is adopted fully in initializing the particles' positions of the next interest point, which effectively improves the speed of the convergence. Experimental results indicate that under the high measurement accuracy without any loss, the time-consumption of this scheme is significantly superior to that of the conventional method, particularly at a large number of interest points. © 2018 SPIE and IS&T [DOI: 10.1117/1.JEI.28.2.021003] [ABSTRACT FROM AUTHOR]