This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Chiu, S.-H. Articles by Wen, C.-Y. Search for Related Content Social Bookmarking                         What's this?

Textural Defect Segmentation Using a Fourier-Domain Maximum Likelihood Estimation Method

Department of Fiber and Polymer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan 10672, Republic of China

Shen Chou

Department of Fiber and Polymer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan 10672, Republic of China

Jiun-Jian Liaw

Department of Fiber and Polymer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan 10672, Republic of China

Che-Yen Wen

Department of Forensic Science, Central Police University, Kuei-Shan, Taoyuan, Taiwan 33334, Republic of China

When automatically inspecting textured surface defects, the most important step is to segment the defects from the background. For complicated textures, however, defect segmentation is still a challenging problem. In this paper, we use a Fourier-domain maximum likelihood estimator (FDMLE) based on the fractional Brownian motion (FBM) model to inspect surface defects of textile fabrics. From the experiments, we obtain good results for defect segmentation, and find the method's performance is invariant under geometric transformation.

Textile Research Journal, Vol. 72, No. 3, 253-258 (2002)
DOI: 10.1177/004051750207200312


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?