Comparative Analysis of Different Fabric Defects Detection Techniques

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Engr Ali Javed 1,* Mirza Ahsan Ullah 1 Aziz-ur-Rehman 1

1. Department of Software Engineering University of Engineering and Technology, Taxila

* Corresponding author.


Received: 27 Sep. 2012 / Revised: 6 Nov. 2012 / Accepted: 6 Dec. 2012 / Published: 8 Jan. 2013

Index Terms

Machine Learning, Computer Vision, multi-layer neural networks, 3D analysis, Novelty Detection, Texture Analysis


In last few years’ different textile companies aim to produce the quality fabrics. Major loss of any textile oriented company occurs due to defective fabrics. So the detection of faulty fabrics plays an important role in the success of any company. Till now most of the inspection is done using human visual. This way is too much time consuming, cumbersome and prone to human errors. In past, many advances are made in developing automated and computerized systems to reduce cost and time whereas, increasing the efficiency of the process. This paper aims at comparing some of these techniques on the basis of classification methods and accuracy.

Cite This Paper

Ali Javed,Mirza Ahsan Ullah,Aziz-ur-Rehman,"Comparative Analysis of Different Fabric Defects Detection Techniques", IJIGSP, vol.5, no.1, pp.40-45, 2013. DOI: 10.5815/ijigsp.2013.01.06


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