Automatic Detection Method for Casting Defects Based on Gradient Features
نویسندگان
چکیده
In this paper, we propose an automated visual inspection method for casting defects. Automatic inspection systems have the potential to significantly improve quality and increase production rates. In our method, the contour discontinuity of casting product and machine-learning-based defect detection are utilized to detect defects on the surface of products. The peripheral vision and involuntary eye microvibration theories of the human visual mechanism in the field of the physiology of vision are modeled and applied in our feature extraction. By using several gradient features and different types of detector, we achieved robust casting defect detection.
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