棉纺织技术2024,Vol.52Issue(12):65-71,7.
基于改进的Hough变换及小波分解的废旧机织物密度检测
Density detection of scrap woven fabric based on improved Hough transform and wavelet decomposition
摘要
Abstract
To achieve high-precision detection of woven fabric density,facilitate the subsequent disassembly and recycling of yarn from waste fabric,the captured original images were first cropped and filtered.In response to the problem of excessive shadow range in the fabric yarn gap,which can easily lead to false detection of straight lines,the traditional Hough line detection algorithm was improved by limiting the angle search range and adding the distance detection function bwdist.Image line detection was performed by detecting the centerline of the connected shadow area,and image skew correction was carried out.Subsequently,the optimal decomposition level of wavelet transform was determined through the method of energy curve.The Graythred function was added in the wavelet transform to determine the optimal threshold for binarization,which could improve the recognition accuracy of the image after wavelet transform processing.The optimal threshold was determined by setting the proportional relationship between 0 and 1 pixel points to achieve image smoothing.Experimental verification showed that compared with manual counting results,the average relative error of warp density recognition was reduced from 5.14%to 2.86%,the average relative error of weft density recognition was reduced from 7.87%to 4.61%before and after the algorithm improvement.It is considered that the detection accuracy of woven fabric density could be improved by the improvement of Hough line detection and wavelet transform algorithms.关键词
废旧纺织品/Hough变换/能量曲线法/小波变换/织物密度/图像处理技术Key words
scrap textiles/Hough transform/energy curve method/wavelet transform/fabric density/image processing technology分类
轻工纺织引用本文复制引用
苑博,杜玉红,董广宇..基于改进的Hough变换及小波分解的废旧机织物密度检测[J].棉纺织技术,2024,52(12):65-71,7.基金项目
国家自然科学基金项目(51205288) (51205288)
天津市研究生科研创新项目(2022BKY140) (2022BKY140)