Fabric defect detection systems and methods—A systematic literature review
| Autor: | Ömer Faruk Özgüven, Kazım Hanbay, Muhammed Fatih Talu |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
Computer science Image processing 02 engineering and technology computer.software_genre Atomic and Molecular Physics and Optics Electronic Optical and Magnetic Materials 020901 industrial engineering & automation Systematic review 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Data mining Electrical and Electronic Engineering Invariant (mathematics) computer |
| Zdroj: | Optik. 127:11960-11973 |
| ISSN: | 0030-4026 |
| DOI: | 10.1016/j.ijleo.2016.09.110 |
| Popis: | This paper presents a comprehensive literature review of fabric defect detection methods First, it briefly explains basic image acquisition system components such as camera and lens. Defect detection methods are categorized into seven classes as structural, statistical, spectral, model-based, learning, hybrid and comparison studies. These methods are evaluated according to such criteria as the accuracy, the computational cost, reliability, rotating/scaling invariant, online/offline ability to operate and noise sensitivity. Strengths and weaknesses of each approach are comparatively highlighted. In addition, the availability of utilizing methods for weaving and knitting in machines is investigated. The available review studies do not provide sufficient information about fabric defect detection systems for readers engaged in research in the area of textile and computer vision. A set of examination for efficient establishment of image acquisition system are added. In particular, lens and light source selection are mathematically expressed. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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