Surface Defect Detection Algorithm Based on Local Neighborhood Analysis

Surface defect detection algorithm based on local neighborhood is proposed to improve the accuracy and real-time of surface defect detection in automation industrial production. A local neighborhood window slides over the entire inspection image, and the coefficient of variation is used as a homogeneity measure. A defect-free region will generate a smaller value of Variation Coefficient than that of a defective region. A simple threshold can thus be used to extract and segment the defective regions. The integral image is introduced to increase the computational efficiency. The proposed algorithm is used to detecting only one single discrimination feature. It could avoid complicated Spectral decomposition and sample learning. Experimental results from material surface detection in the industry, has shown the feasibility and effectiveness.