Crack Contour Modeling Based on a Metaheuristic Algorithm and Micro-Laser Line Projection

Currently, bio-inspired metaheuristic algorithms play an important role in computer vision for assessing surface cracks. Also, manufacturing industries need non-destructive technologies based on biomimetics theory for characterizing micro-crack contours to determine surface quality. In this way, it is necessary to develop bio-inspired algorithms to construct crack contour models for determining crack regions through an optical microscope system. In this study, a metaheuristic genetic algorithm is implemented to build crack contour models by means of Bezier functions and crack coordinates. The contour modeling is performed by a microscope vision system based on micro-laser line scanning, which provides the crack coordinates through a broken laser line in the crack region. Thus, the metaheuristic algorithm builds the crack contour model by fitting the Bezier functions toward the crack topography. At this stage, an objective function moves the Bezier functions toward the crack topography via control points. The proposed technique provides micro-scale crack contours with a relative error smaller than 2%. Thus, the proposed crack contour modeling enhances the traditional crack contour inspection based on microscope image processing. This contribution is supported by a comparison between the proposed technique and the crack characterization performed via conventional image processing algorithms.