Grey Relational Analysis of an Automatic Identifying System for Clothing Texture
Research and development
Authors:
- Su Te-Li
Department of Cosmetic Application and Management, St. Mary’s Medicine, Nursing and Management Collage, Yilan, Taiwan R. O. C. - Kuo Yu-Lin
Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan R. O. C. - Chen Hua-Wei
Department of Cosmetic Application and Management, St. Mary’s Medicine, Nursing and Management Collage, Yilan, Taiwan R. O. C. - Kung Fu-Chen
Center for General Educationm, Kainan University, Taoyuan County, Taiwan R. O. C.
 Full text | Abstract: Abstract: Fabric quality inspection is important to the textile industry because the price of second-quality fabric is merely 45% to 65% of that of fi rst-quality fabric. Using the wavelet transform, this paper intends to analyse fabric images and establish the different features of fabric texture, and then through grey relational analysis of grey theory, we will attempt to distinguish and classify the texture of fabrics, mainly cotton, polyester, silk, rayon, knitting and linen. The grey relational analysis approach is applied to analyse the correlation in the random factor sequence of feature indexes after some data processing and determine the texture type of the designated fabric on the basis of the highest correlative degree. Experiment fi ndings show that the automatic distinguishing system for the fabric types discussed in this paper is capable of distinguishing six different textile images. |
Tags: fabric texture, automatic distinguishing system, wavelet transform, grey relational analysis
Citation: Su T.-L., Kuo Y.-L., Chen H.-W., Kung F.-C.; Grey Relational Analysis of an Automatic Identifying System for Clothing Texture. FIBRES & TEXTILES in Eastern Europe 2010, Vol. 18, No. 2 (79) pp. 60-64.