JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2014, Vol. 44 ›› Issue (4): 1-8.doi: 10.6040/j.issn.1672-3961.2.2013.344

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A novel fabric defect detection algorithm based on textural differential visual saliency model

LI Chunlei1, ZHANG Zhaoxiang2, LIU Zhoufeng1, LIAO Liang1, ZHAO Quanjun1   

  1. 1. School of Electronic and Information Engineering, Zhongyuan University of Technology, Zhengzhou 450007, Henan, China;
    2. School of Computer Science and Engineering, Beihang University, Beijing 100191, China
  • Received:2013-04-30 Revised:2014-06-26 Online:2014-08-20 Published:2013-04-30

Abstract: In order to effectively detect defect for fabirc image with variety of defects and complex texture, a novel fabric defect detection scheme based on textural difference-based visual saliency model was proposed, which considered the characteristics of fabric image and human visual perception. First, the test image was split into image blocks, and textural feature was extracted using LBP operator for each image block. Second, saliency was calculated by comparing their textural feature with the average texture feature. Finally, the threshold segmentation algorithm was used to localize the defect region. Comparing with the current saliency model, the proposed saliency model could effectively distinguish the defect. In addition, segmentation scheme was superior to the current defect detection algorithm in detection and localization.

Key words: fabric defect, defect detection, textural difference, segment, visual saliency, local binary pattern

CLC Number: 

  • TP391
[1] MARK K, PENG P, YIU K. Fabric defect detection using morphological filters[J]. Image and Vision Computing, 2009, 27(10):1585-1592.
[2] 邹超,朱德森,肖力. 基于模糊类别共生矩阵的纹理疵点检测方法[J]. 中国图象图形学报, 2007, 12(1):92-97. ZOU Chao, ZHU Deshen, XIAO Li. Textural defect detection based on fuzzy label co-occurrence matrix[J]. Journal of Image and Graphics, 2007, 12(1):92-97.
[3] ZHANG Y, LU Z, LI J. Fabric defect detection and classification using gabor filters and gaussian mixture model[C]//Asian Conf. Computer Vision. Xi'an, Shaanxi, China: Springer, 2009:635-644.
[4] SRIKAEWL A, ATTAKIMONGCOL K, KUMSAWAT P, et al. Detection of defect in textile fabrics using optimal gabor wavelet network and two-dimensional PCA[C]//International Symposium on Visual Computing. Las Vegas, Nevada, USA: Springer, 2011: 436-445.
[5] TOLBA A. Fast defect detection in homogeneous flat surface products[J]. Expert Systems with Applications, 2011 (38): 12339-12347.
[6] CHAN H Y, RAJU C, SARI-SARRAF H, et al. A general approach to defect detection in textured materials using a wavelet domain model and level sets[C]//International Society for Optics and Photonics. Boston, Massachusetts, USA: SPIE, 2005:60010D-60010D-6.
[7] ZHANG Y, LU Z, LI J. Fabric defect classification using radial basis function network[J]. Pattern Recognition Letters, 2010, 31(13):2033-2042.
[8] HOU X, ZHANG L. Saliency detection: a spectral residual approach[C]//IEEE Conference on Computer Vision and Pattern Recognition. Minneapolis, Minnesota, USA: IEEE, 2007:1-8.
[9] ACHANTA R, HEMAMI S, ESTRADA F, et al. Frequency-tuned salient region detection[C]//IEEE Conference on Computer Vision and Pattern Recognition. Miami, Florida, USA: IEEE, 2009:1597-1604.
[10] JUNG C, KIM C. A unified spectral-domain approach for saliency detection and its application to automatic object segmentation[J]. Image Processing, IEEE Transactions on, 2012, 21(3):1272-1283.
[11] HOU X, HAREL J, KOCH C. Image signature: highlighting sparse salient regions[J]. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2012, 34(1):194-201.
[12] SEO H J, MILANFAR P. Static and space-time visual saliency detection by self-resemblance[J]. Journal of Vision, 2009, 9(12):15-21.
[13] HOU X, ZHANG L. Dynamic visual attention: searching for coding length increments[C]// NIPS. Vancouver, B.C., Canada: MIT Press, 2008:5-7.
[14] WNG W, CHEN C, WANG Y, et al. Simulating human saccadic scanpaths on natural images[C]// IEEE Conference on Computer Vision and Pattern Recognition. Colorado Springs, CO, USA: IEEE, 2011:441-448.
[15] GOPALAKRISHNAN V, HU Y, RAJAN D. Random walks on graphs for salient object detection in images[J]. Image Processing, IEEE Transactions on, 2010, 19(12):3232-3242.
[16] PORWAY J, WANG Q, ZHU S C. A hierarchical and contextual model for aerial image parsing[J]. International Journal of Computer Vision, 2010, 88(2):254-283.
[17] GOFERMAN S, ZELNIK M L, TAL A. Context-aware saliency detection[J]. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2012, 34(10):1915-1926.
[18] 黄志勇, 何发智, 蔡贤涛, 等. 一种随机的视觉显著性检测算法[J]. 中国科学: 信息科学, 2011, 41(7):863-874. HUANG Zhiyong, HE Fazhi, CAI Xiantao, et al. Efficient random saliency map detection[J]. Science China Information Sciences, 2011, 41(7):863-874.
[19] KIM W, KIM C. Saliency detection via textural contrast[J]. Optics Letters, 2012, 37(9):1550-1552.
[20] BORJI A, ITTI L. Exploiting local and global patch rarities for saliency detection[C]//IEEE Conference on Computer Vision and Pattern Recognition, Providence. Rhode Island, USA: IEEE, 2012:478-485.
[21] MURRAY N, VANRELL M, OTAZU X, et al. Saliency estimation using a non-parametric low-level vision model[C]//IEEE Conference on Computer Vision and Pattern Recognition. Colorado Springs, CO, USA: IEEE, 2011:433-440.
[22] OJALA T, PIETIKAINEN M, MAENPAA T. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns[J]. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2002, 24(7):971-987.
[23] OTSU N. A threshold selection method from gray-level histograms[J]. Automatica, 1975, 11(285-296):23-27.
[24] NG F. Automatic thresholding for defect detection[J]. Pattern Recognition Letters, 2006, 27(14):1644-1649.
[25] LIU Z, WANG J, ZHAO Q, et al. A fabric defect detection algorithm based on improved valley-emphasis method[J]. Research Journal of Applied Sciences, Engineering and Technology, 2014, 7(12):2427-2431.
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