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Automatic Defect Detection of Patterned Fabric by using RB Method and Independent Component Analysis
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 39 - Number 18 |
| Year of Publication: 2012 |
| Authors: R K Rao Ananthavaram, O.Srinivasa Rao, MHM Krishna Prasad |
10.5120/5084-7422
|
R K Rao Ananthavaram, O.Srinivasa Rao, MHM Krishna Prasad . Automatic Defect Detection of Patterned Fabric by using RB Method and Independent Component Analysis. International Journal of Computer Applications. 39, 18 ( February 2012), 52-56. DOI=10.5120/5084-7422
Abstract
Automatic fabric inspection is important for maintain the fabric quality. For a long time the fabric defects inspection process is still carried out with human visual inspection, and thus, insufficient and costly. Hence the automatic fabric defect inspection is required to reduce the cost and time waste caused by defects. The development of fully automated web inspection system requires robust and efficient fabric defect detection algorithms. The detection of local fabric defects is one of the most intriguing problems in computer vision. Texture analysis plays an important role in the automated visual inspection of texture images to detect their defects. The main aim of this study is to find independent components of the Regular Bands method of the patterned fabric images for the purpose of defect detection in this paper, Independent Component Analysis (ICA) is the proposed method that solves the problem of defect detection in patterned fabrics prior to Regular Bands (RB) method. Patterned fabric is built on the repetitive unit of its design. RB is an existing method that is based on periodicity. The proposed method ICA along with RB method tries to improve the efficiency and quality of the fabric with in less time.
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