摘要
在计算机图像处理和横式识别领域，快速富氏变换（ＦＦＴ）技术起着非常重要的作用．织物（此文只论及机织物）的结构是由相同单元规则地排列而成的，呈现很强的周期性．这使得ＦＦＴ技术在分析织物结构特征中特别有效．本文讨论如何应用ＦＦＴ去识别织物组织、纱线密度、纬纱倾斜度等其它结构参数．
he Fast Fourier Transfrom (FFT)plays a very important role in image processingand pattern recognition.Since a woven fabric consists of regular repeating units,the FFT is parhcularly useful for analyzing periodicity, directionality and spacing of repeating units in the fabric.This paper describes procedures of applying FFT techniques in image processing to identify weavepattern, fabric count, yarn skewness and other structural characteristics of woven fabrics. A colorscanner is used to digitize fabric images (two-dimensional functions in a spatial domain), and a customized software package is used to perform the FFT on the images. A power spectrum image is derived from the FFT of an image, and considered a two-dimensional function in a frequency domain. Peaks in the power spetrum image stand for frequency terms of periodic elements, fromwhich basic weavepatterns (e. g. , plain, twill,satin,etc. )can be recognized. A radial functionand an angular function,derived from the power spectrum, are used to measure the coarseness andthe directionality of the periodic elements. By selecting power peaks in a certain direction to reconstruct the image , warp or weft elements can be extracted to facilitate fabric count and skewness measurements. Fourier filtering, image filtering in the frequency domain, is used to suppress noise andto select features that have a certain range of frequencies. Fabrics with various weave patterns andyarn counts were tested using the FFT techniques.
出处
《西北纺织工学院学报》
1996年第4期343-352,共10页
Journal of Northwest Institute of Textile Science and Technology
