Journal article
Automated inspection of textile fabrics using textural models
IEEE transactions on pattern analysis and machine intelligence, v 13(8), pp 803-808
Aug 1991
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The authors discuss the problem of textile fabric inspection using the visual textural properties of the fabric. The problem is to detect and locate the various kinds of defects that might be present in a given fabric sample based on an image of the fabric. Stochastic models are used to model the visual fabric texture. The authors use the Gaussian Markov random field to model the texture image of nondefective fabric. The inspection problem is cast as a statistical hypothesis testing problem on statistics derived from the model. The image of the fabric patch to be inspected is partitioned into nonoverlapping windows of size N*N where each window is classified as defective or nondefective based on a likelihood ratio test of size alpha . The test is recast in terms of the sufficient statistics associated with the model parameters. The sufficient statistics are easily computable for any sample. The authors generalize the test when the model parameters of the fabric are assumed to be unknown.< >
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Details
- Title
- Automated inspection of textile fabrics using textural models
- Creators
- F.S. Cohen - Drexel UniversityZ. Fan - Xerox (United States)S. Attali - Gfi Informatique (France)
- Publication Details
- IEEE transactions on pattern analysis and machine intelligence, v 13(8), pp 803-808
- Publisher
- IEEE
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:A1991GC64200005
- Scopus ID
- 2-s2.0-0026202332
- Other Identifier
- 991020531867604721
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- Collaboration types
- Industry collaboration
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Engineering, Electrical & Electronic