Algorithm for Fabric Defect Detection based on Relative Total Variation and Adaptive Threshold Segmentation
In the textile industry,intelligent detection of fabric defects remains a formidable challenge.To automate the detection of fabric defects,we propose an algorithm based on the relative total variation model and adaptive threshold segmentation.This approach utilizes median filtering for noise reduction,enhances fabric defects using the relative total variation model to suppress background textures,and analyzes the grayscale histogram of the enhanced defect image.Through iterative adaptive threshold segmentation,a binary image of defects is obtained.Testing on various types of defect images demonstrates that this algorithm effectively enhances and segments defects,yielding promising detection outcomes.
defect detectionmedian filteringrelative total variation modeladaptive threshold segmentation
万方数据
维普
