Model-based methods for textile fault detection

J. G. Campbell, C. Fraley, D. Stanford, F. Murtagh, A. E. Raftery

Research output: Contribution to journalArticlepeer-review

36 Citations (Scopus)


Addressing the problem of automatic fault detection in woven and dyed fabric, we discuss a number of new statistical model-based methods and relate them to a first stage of point/local detection and a second stage of extended pattern detection. One model-based method defines a maximum likelihood binarization of the image. In another model-based method, we describe a discrete Fourier transform-based texture analysis technique that is highly effective for woven textiles in discriminating subtle flaw patterns from the pronounced background of repetitive weaving pattern and random clutter. Finally, we describe a model-based clustering method that can be employed to aggregate perceptual groupings of point and local detections.

Original languageEnglish
Pages (from-to)339-346
Number of pages8
JournalInternational Journal of Imaging Systems and Technology
Issue number4
Publication statusPublished - 2 Jul 1999
Externally publishedYes


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