Paper Defect Detection Algorithm Based on the Mathematical Morphology and Computer Vision

Abstract

Abstract A method for detecting paper’s surface defects is proposed, which is based on mathematical morphology algorithm and computer vision technique. Firstly, the mean filtering and wavelet denoising in image pre-processing are used to eliminate the image noise, and wavelet analysis can achieve image enhancement and increase the contrast between the target area and the background. And then, an improved threshold Canny operator is used to segment the image to extract the complete scratch line and other defect edges. Finally, the target region features are coloured by mathematical morphology processing. The method’s stimulating result is verified in the Matlab software, from which we can conclude that the method’s detecting effect is very effective.