Model-based methods for textile fault detection

✍ Scribed by J. G. Campbell; C. Fraley; D. Stanford; F. Murtagh; A. E. Raftery

• Publisher: John Wiley and Sons
• Year: 1999
• Tongue: English
• Weight: 334 KB
• Volume: 10
• Category: Article
• ISSN: 0899-9457
• DOI: 10.1002/(sici)1098-1098(1999)10:4<339::aid-ima5>3.0.co;2-3

✦ Synopsis

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.