摘要
应用自适应小波变换技术以实现机织物密度的自动测量。先运用Wiener2和直方图均衡技术对织物图像进行预处理,增强图像的纹理特征;接着选取自适应小波技术对织物图像进行分解;再对分解得到的子图像进行二值、平滑等后处理;最后通过分析后处理图像的经纬纱线信息得到织物密度。试验结果证明,运用该方法能够准确测量3种基本组织的织物密度,是一种行之有效的方法。另外,还简要介绍了自适应小波的构造技术。
By using computer image processing and analysis, a method to measure woven fabric density is developed in this study. Firstly, the fabric image is pre-processed by Wiener2 and histogram equalization to make more clear the fabric texture features; Secondly, the pre-processed woven image is decomposed into horizontal and vertical sub-image based on adaptive wavelet; Thirdly, the features are extracted from the subimages through some treatments like smoothing; Finally, the fabric density can be obtained by analyzing these features of warps and wefts of the fabric. The experiments have proved that this method can exactly measure the density of three kinds of woven fabric with basic structure. In addition, this paper also presents how to construct the adaptive wavelets.
出处
《纺织学报》
EI
CAS
CSCD
北大核心
2007年第2期32-35,共4页
Journal of Textile Research
关键词
小波变换
自适应小波
图像处理
织物
密度
测量
wavelet transform
adaptive wavelet
image processing
fabric
density
measure
