Automated inspection of textile defects using independent component analysis

The paper addresses a new defect detection method that uses independent component analysis (ICA) for locating and also partially identifying defects in textile fabric images. The method is based on obtaining ICA basis vectors for a large number of textile images obtained from the same fabric. Feature vectors are computed for the test images and these are compared with the true feature vector predetermined from a defect-free image. The proposed method is shown to be invariant under rotation. Experimental results are also presented to demonstrate the use of this method for visual inspection of textile products obtained from a real factory environment.