Effective Segmentation in Plain woven Fabric Defect Detection by using Digital Image Processing
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2018 by IJCTT Journal|
|Year of Publication : 2018|
|Authors : S.Sahaya Tamil Selvi, Dr.G.M.Nasira|
|DOI : 10.14445/22312803/IJCTT-V59P102|
S.Sahaya Tamil Selvi, Dr.G.M.Nasira "Effective Segmentation in Plain woven Fabric Defect Detection by using Digital Image Processing". International Journal of Computer Trends and Technology (IJCTT) V59(1):8-14, May 2018. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Quality control is an important issue in the garments industry. In the past two decades during which computer vision based inspection has become one of the most important application areas. Fabric industry is one of the most important field in identifying defects or flaws. But these days lot of work can be done on to remove defects in images of fabric in fabric industry and calculate defective areas in fabric images more precisely. This paper proposes, a user friendly MATLAB based graphical user interface (GUI) that segments the defected area of a fabric image using Entropy filter method. From the segmented image, features of defected area such as area, entropy, standard deviation, smoothness, skewness, GLCM, max intensity, min intensity, mean, standard deviation and energy are calculated, for classification of images as defected or not. Also accuracy, specificity and sensitivity are calculated with respective to ground truth, for the performance evaluation. The GUI is implemented satisfactorily using MATLAB.
 Priyanka Vyas, Manish Kakhani, “Fabric fault processing using image processing techniques”, International Journal of Multidisciplinary Research and Development 2015;2(2):29-31.
 KL. Mak, P. Peng, KF.C. Yiu, “Fabric defect detection using morphological filters”, Image and Vision Computing 2009, 1585-1592.
 Kumar T.A, Paul. V., Priya S, “A novel approach to fabric defect detection using digital image processing”, Signal Processing, Communication, Computing and Networking Technologies (ICSCCN), 2011.
 Harjot Singh, Prabhpreet Kaur, “Improved Visibility Restoration Using Edge Preserving Guided Filter”, International Journal of Emerging Trends & Technology in Computer Science (IJCTTCS), Vol. 3, Issue 2 March – April 2014 Page 85 ISSN 2278-6856.
 S Shruti Gandhi, Sonal Doomra, Akash Tayal and Ashwini Kumar, “A Novel Hénon Map Based Adaptive PSO for Wavelet Shrinkage Image Denoising”, BVICAM’s International Journal of Information Technology BIJIT, July-December, 2013; Vol. 5 No.2; ISSN 0973-5658.
 Jia He, Qian Jiang, “Research on the Fabric Defect Detection Method based on Improved PSO and NN Algorithm”, International Journal of Digital Content Technology and its Applications(JDCTA) Vol. 6, No. 8, May 2012 doi:10.4156/jdcta.vol6.issue8.21.
 P. Banumathi, Dr. G. M. Nasira, “Fourier Transform and Image Processing in Automated Fabric Defect Inspection System”, International Journal of Computational Intelligence and Informatics,(IJCII) Vol. 3, Issue 1(April-June 2013)ISSN: 2349-6363.
 Dr. G. M. Nasira, P. Banumathi, “Automatic Defect Detection Algorithm For Woven fabric using Artificial Neural Network Techniques”, International Journal of Innovative Research in Computer and Communication Engineering (IJICRCCE) Vol. 2, Issue 1 (January 2014) ISSN: 2320 – 9798.
 S.Sahaya Tamil Selvi, Dr.G.M.Nasira, “Noise removal of Fabric images in Automated Fabric Inspection System using Digital Image Processing Techniques”, International Journal of Applied Engineering Research(IJAER),ISSN:0973-4562,Vol 10 No.69(2015).
 Jagrti Patel, Meghna Jain, PapiyaDutta, “Fault Detection Using Graph Based Segmentation”, International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), Vol. 2, Issue 11, November 2013, ISSN:2278-1323
 S.Sahaya Tamil Selvi, “Particle Swarm Optimization enabled Filtering for Fabric Images in Automated Fabric Inspection System”, IEEE Xplore, INSPEC Accession Number: 16426564
 R.Gonzales and R. Woods – Digital Image Processing; Prentice Hall of India, 2008.
 S.E. Umbough – Computer Vision and Image Processing; Englewood Cliffs, Nj: Prentice- Hall, 1998.
Fabric defect, Entropy filtering, Standard deviation filtering, Range filtering, Segmentation, True positive, True Negative, Sensitivity