title   
  

Independent component analysis for texture defect detection

Sezer, Osman Gökhan and Ertüzün, Ayşın and Erçil, Aytül (2004) Independent component analysis for texture defect detection. Pattern Recognition and Image Analysis, 14 (2). pp. 303-307. ISSN 1054-6618

[img]PDF - Repository staff only - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
272Kb

Abstract

In this paper, a novel method for texture defect detection is presented. The method makes use of Independent Component Analysis (ICA) for feature extraction from the nonoverlapping subwindows of texture images and classifies a subwindow as defective or nondefective according to Euclidean distance between the feature obtained from average value of the features of a defect free sample and the feature obtained from one subwindow of a test image. The experimental results demonstrating the use of this method for visual inspection of textile products obtained from a real factory environment are also presented.

Item Type:Article
Subjects:T Technology > T Technology (General)
ID Code:392
Deposited By:Aytül Erçil
Deposited On:17 Feb 2007 02:00
Last Modified:16 Oct 2007 12:06

Repository Staff Only: item control page