In this paper, an intelligent color-textured fabric defect detection and classification model using genetic algorithms and the Elman neural network is introduced. A color ring projection is used for image processing, and the solution for optimization of parameters is based on the genetic algorithm method. The new modified Elman network is proposed to classify the type of fabric defects, which have proportional, integral, and derivative properties. The proposed inspecting model in this study is more feasible and applicable in fabric and stitching garment defect detection and classification.
Dorrity JL, Vachtsevanos G. and Jasper W.Real-time fabric defect detection and control in weaving process. Nat Textil Center Annu Rep1994; 20: 193-202.
2.
Munden L. and Norton WLMachine vision in textile manufacture. Textil Asia1988; 19: 85-88.
3.
Sirikasemlert A. and Tao XMObjective evaluation of textural changes in knitted fabrics by laser triangulation. Textil Res J2000; 70: 1076-1087.
4.
Rohrmus D.Invariant texture features for web defect detection and classification . SPIE Proc Mach Vision Syst Inspection Metrol1999; 38: 144-155.
5.
Song KY, Kittler J. and Petrou M.Defect In random colour textures. Image Vision Comput1996; 60: 667-683.
6.
Arivazhagan S. and Ganesan L.Texture segmentation using wavelet transform . Pattern Recognit Lett2003; 24: 3197-3203.
7.
Kumar A.Inspection of surface defects using optimal FIR filters In. Proceedings of the 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003; 3(2): 241-244.
8.
Jain AK and Farrokhnia F.Unsupervised texture segmentation using Gabor filters. Pattern Recognit1991; 24: 1167-1186.
9.
Suen PH and Healey G.Modeling and classifying color textures using random fields in a random environment . Pattern Recognit1999; 32: 1009-1017.
10.
Panjwan DK and Healey G.Markov random field for unsupervised segmentation of texture color images . IEEE Trans Pattern Anal Mach Intell1995 ; 17: 939-954.
11.
Sengur A.Wavelet transform and adaptive neuro-fuzzy inference system for color texture classification. Expert Syst Appl, 2007; 34: 2120-2128.
12.
Escofet J., Navarro RB, Millan MS and Pladellorens JMDetection of local defects in textile webs using Gabor filter. Proc SPIE1996; 2785: 163-170.
13.
Thai B. and Healey G.Optimal spatial filter selection for illumination-invariant color texture discrimination. IEEE Trans Syst Man Cybern Part B Cybern2000; 30: 7610-7616.
14.
Kim SC and Kang TJFabric surface roughness evaluation using wavelet-fractal method: part II: fabric pilling evaluation. Textil Res J2005 ; 75: 761-770.
15.
Tsai IS and Hu MCAutomatic inspection of fabric defects using an artificial neural network technique. Textil Res J1996; 66: 474-482.
16.
Tsai DM and Chiang CHAutomatic band selection for wavelet reconstruction in the application of defect detection. Image Vision Comput2003 ; 21: 413-431.
17.
Ngan YT, Pang KH, Yung SP and Ng K.Wavelet based methods on patterned fabric defect detection. Pattern Recognit2005; 38: 559-576.
18.
Yuen CWM, Wong WK and Qian SQA hybrid model using genetic algorithm and neural network for classifying garment defects. Expert Syst Appl2008; 36: 2037-2047.
19.
Shiau YR, Tsai IS and Lin CSClassifying web defects with a back-propagation neural network by color image processing. Textil Res J2000; 70: 633-640.
20.
Boukouvalas C., Kittler J., Marik R. and Petrou M.Color grading of randomly textured ceramic tiles using color histograms. IEEE Trans Ind Electron1999; 46: 219-226.
21.
Caelli T. and Reye D.On the classification of image regions by colour texture and shape . Pattern Recognit1993; 26: 461-470.
22.
Tang YY, Li BF, Ma H. and Liu J.Ring-projection-wavelet-fractal signatures: a novel approach to feature to feature extraction. IEEE Trans Circuits Syst Analog Digital Signal Process1998; 45: 1130-1134.
23.
Tan SC and Kittler J.On colour texture representation and classification In. Proceedings of the 2nd International Conference on Image Processing1992; 390-395.
24.
Inui S.A computer aided system using a genetic algorithm applied to apparel design . Sen’i Gakkaishi1994; 50: 593-598.
25.
Zhang YF and Bresee RRFabric defect detection and classification using image analysis. Textil Res J1995; 65(1): 1-9.
26.
Jasper W., Joines J. and Brenzovich J.Fabric defect detection using a genetic algorithm tuned wavelet filter . J Textil Inst2005; 96: 43-54.
27.
Bounsaythip C. and Alander JTGenetic algorithms applied to image processing In. Proceedings of the 3rd Nordic Workshop on Genetic Algorithms1997; 14: 423-431, Helsinki .
28.
Elman J.Finding structure in time. Cognitive Sci1994 ; 14: 179-211.
29.
Sastry PS, Santharam G. and Unnikrishnan KPMemory neuron networks for identification and control of dynamic systems . IEEE Trans Neural Networks1994; 5: 306-319.
30.
Cheng YC, Qi WM and Jie Z.A new Elman neural network and its dynamic properties. IEEE Conf Cybern Intell2008; 70: 971-975.
31.
Wong WK, Yuen CWM and Fan DDStitching inspection using segmented windows technique and BP neural network . Expert Syst Appl2009; 36: 3845-3856.
32.
Shady E., Gowayed Y., Abouiiana M., Youssef S. and Pastore C.Detection and classification of defects in knitted fabric structures . Textil Res J2006; 76: 295-300.
