A novel thermal-based fabric defect detection technique

During the fabric production process, many defects can be occurred stemming from the unevenness in spinning, weaving, finishing processes, or from the raw materials. The fabric quality control process for the detection of these defects is carried out by specialist operators. In this paper, a new method based on the use of thermal camera for detecting these defects from the textile fabric images is presented. For identification process of defective area, fabric images were obtained by a thermal camera during the fabric flow in quality control machine that was specially designed for this experiment. Defective and defect-free regions on fabric surface were determined by thermal camera due to the thermal differences. The mentioned thermal defect detection system will eliminate the worker usage for fabric quality control process, thus it will provide a cost-effective and competitive manufacturing.

[1]  H. Saunders,et al.  Digital Signal Processing (2nd Edition) , 1988 .

[2]  Mohammed Bennamoun,et al.  Optimal Gabor filters for textile flaw detection , 2002, Pattern Recognit..

[3]  Khan M. Iftekharuddin,et al.  Field Guide to Image Processing , 2012 .

[4]  Jing Wang,et al.  Fabric defect detection using Gabor filters and defect classification based on LBP and Tamura method , 2013 .

[5]  Eleftherios Kayafas,et al.  A computer vision approach for textile quality control , 2001, Comput. Animat. Virtual Worlds.

[6]  Jianli Liu,et al.  Fabric defect segmentation by bidimensional empirical mode decomposition , 2014 .

[7]  E. Shady,et al.  Detection and Classification of Defects in Knitted Fabric Structures , 2006 .

[8]  Mark S. Nixon,et al.  Basic image processing operations , 2013 .

[9]  Thanos Stouraitis,et al.  Defect detection and classification on web textile fabric using multiresolution decomposition and neural networks , 1999, ICECS'99. Proceedings of ICECS '99. 6th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.99EX357).

[10]  Ajay Kumar,et al.  Defect detection in textured materials using Gabor filters , 2000, Conference Record of the 2000 IEEE Industry Applications Conference. Thirty-Fifth IAS Annual Meeting and World Conference on Industrial Applications of Electrical Energy (Cat. No.00CH37129).

[11]  Roland T. Chin Automated visual inspection techniques and applications: A bibliography , 1982, Pattern Recognit..

[12]  Randall R. Bresee,et al.  Fabric Defect Detection and Classification Using Image Analysis , 1995 .

[13]  S. Gryś,et al.  Filtered thermal contrast based technique for testing of material by infrared thermography , 2011 .

[14]  Wang Jianxia,et al.  Fabric Defect Detection Method Based on Image Distance Difference , 2007, 2007 8th International Conference on Electronic Measurement and Instruments.

[15]  Jun Wang,et al.  Fabric defect detection using adaptive dictionaries , 2013 .

[16]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[17]  Jovan Bojkovski,et al.  Thermal imaging in medicine , 2015 .

[18]  Rafael C. González,et al.  Digital image processing using MATLAB , 2006 .

[19]  S. A. Hosseini Ravandi,et al.  Fourier Transform Analysis of Plain Weave Fabric Appearance , 1995 .

[20]  Hemdan A. Abou-Taleb,et al.  ON-LINE FABRIC DEFECT DETECTION AND FULL CONTROL IN A CIRCULAR KNITTING MACHINE , 2008 .

[21]  Allan Hanbury,et al.  Finding defects in texture using regularity and local orientation , 2002, Pattern Recognit..

[22]  Bülent Sankur,et al.  Survey over image thresholding techniques and quantitative performance evaluation , 2004, J. Electronic Imaging.

[23]  Errol J. Wood,et al.  Applying Fourier and Associated Transforms to Pattern Characterization in Textiles , 1990 .

[24]  Wenliang Xue,et al.  Intelligent detection of defects of yarn-dyed fabrics by energy-based local binary patterns , 2012 .

[25]  Grantham K. H. Pang,et al.  Discriminative fabric defect detection using adaptive wavelets , 2002 .

[26]  Li Tan,et al.  Image Processing Basics , 2013 .

[27]  Josef Krautkrämer,et al.  Detection and Classification of Defects , 1990 .

[28]  Miquel Ralló,et al.  Wavelet based techniques for textile inspection , 2002 .

[29]  Michal Bednarek,et al.  Processing and recognition of the thermal images using wavelet transforms , 2011, Microelectron. Reliab..

[30]  Nelson H. C. Yung,et al.  Robust fabric defect detection and classification using multiple adaptive wavelets , 2005 .

[31]  Jirí Mekyska,et al.  On the focusing of thermal images , 2011, Pattern Recognit. Lett..

[32]  Carlo Poggi,et al.  Damage and Defect Detection Through Infrared Thermography of Fiber Composites Applications for Strengthening of Structural Elements , 2013 .

[33]  Mark S. Nixon,et al.  Feature extraction & image processing for computer vision , 2012 .

[34]  Re Gonzalez,et al.  R.C. Eddins, Digital image processing using MATLAB, vol. Gatesmark Publishing Knoxville , 2009 .