Surface Defect Detection Based on Gradient LBP

Abstract

The LBP histogram obtained based on the local binary pattern (LBP) method usually has a higher dimension, and not conducive to calculation. The LBP method adopts the gray difference value between single points as the LBP output value, which is not robust to noise and illumination. Therefore, this paper improves the traditional LBP method and proposes a surface defect detection method based on gradient local binary pattern (GLBP), which uses image sub-blocks to reduce the dimensionality of the LBP data matrix. The method adopts weighted binary output values in eight directions within the neighborhood to indicate local gray changes, which suppresses the effects of light and noise on the detection results. Experiments show that the method can determine the defect location well and provide good feature information for subsequent defect classification.