一种基于小波变换的织物组织与结构参数检测方法

织物组织结构及参数的正确识别与分析是一项费时而又重要的工作。本文提出了一种运用图像处理技术检测织物纹理方向、识别织物组织以及经纬密测量的新方法。把小波变换对织物图像信号良好的分解性能与Radon变换对纹理直线的检测特性结合，运用于织物纹理方向的检测分析、织物组织识别及经纬密测量。相关实验表明该方法不仅能较准确测定纹理方向和经纬密等结构参数，而且其检测的结果能为正确推断与识别织物所属的基本组织类型提供有效依据。

Detection method for fabric weave patterns and structural parameters based on wavelet transform

It is an important but time-consuming job to recognize and analyze the fabric weave patterns and texture parameters correctly. A novel approach for detecting fabric texture directions, recognizing weave patterns and measuring yarn density is proposed using image-processing technology. Wavelet transform, which is suitable for fabric image signal decomposition, and Radon transform, which is suitable for fabric texture line detection, are combined together and used for fabric texture line detection, weave pattern recognition and yarn density measurement. Related experimental results show that the proposed method can obtain accurate measurement results, and provide effective foundation for recognizing basic fabric weave type.