Curvelet transforms and flower pollination algorithm based machine vision system for roughness estimation

摘要: Machine vision based systems aided in approximation of the surface roughness a nondestructive means and relieved process automation. The advent computers computational tools manufacturing, assisted reduction ideal time by their knack to estimate micron level uncertain line values roughness. In present work, develop machine intelligent estimation system; high-resolution images are captured. captured processed MATLAB image processing toolbox for Curvelet Transform texture features. measured features mapped using advanced tool Flower Pollination Algorithm (FPA). FPA closely estimated with precise percentile error when compared another support vector model.