The invention relates to the technical field of
computer vision, in particular to a defect segmentation positioning method and
system for an inorganic mineral
casting image, and the method comprises the following steps: calling an illumination image to analyze brightness, matching
exposure parameters, splicing the image, analyzing a gradient, recognizing a defect, screening an effective region, calculating a gray variance, and constructing roughness weight recognition texture features. According to the method, the high-reflection area identification, the
brightness gradient analysis, the pixel-level roughness weight and the
structure tensor analysis are combined, the
exposure interval can be dynamically adjusted when the
casting image is processed, the defect type information is output in the direction, and the positioning information is generated by correcting the recognition position in combination with the actual coordinate of the target spot. The method has the advantages that the high-reflection area identification, the
brightness gradient analysis, the pixel-level roughness weight and the
structure tensor analysis are combined; the method has the advantages that the method is simple and easy to implement, detail loss of overexposure areas is reduced, the recognition precision of defect areas is improved, accurate area segmentation and classification
processing are achieved, roughness weight calculation combining gray variance and
pixel density is combined, the sensitivity to surface fine defects is enhanced, and the precision and reliability of defect positioning are improved.