Fast segmentation of foreign fiber image

IFIP Advances in Information and Communication Technology

Volumn 370 AICT, Issue PART 3, 2012, Pages 469-483

  Wu, Yutao ^a   Yang, Wenzhu ^a   Li, Zhenbo ^a   Li, Daoliang ^a  

^a CHINA AGRICULTURAL UNIVERSITY   (China)

Author keywords

background extraction; Cotton; Fast segmentation; Foreign fibers; image block; image processing; Ostu method

Indexed keywords

AUTOMATED INSPECTION; BACKGROUND EXTRACTION; COLOR IMAGES; CONVENTIONAL METHODS; FOREIGN FIBER; GRAY-LEVEL; GRAY-SCALE IMAGES; IMAGE BLOCKS; IMAGE TRANSFORMATIONS; OSTU METHOD; OTSU'S METHOD; PIECEWISE LINEAR; TARGET IMAGES;

AGRICULTURE; COTTON; FIBERS; IMAGE PROCESSING; INSPECTION; PIECEWISE LINEAR TECHNIQUES; TEXTILE INDUSTRY;

IMAGE SEGMENTATION;

AGRICULTURE; COTTON; FIBERS; IMAGE ANALYSIS; INSPECTION;

EID: 84870485327     PISSN: 18684238     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-27275-2_53     Document Type: Conference Paper

References (18)

1. Abouelela, A., Abbas, H. M., Eldeed, H., Wahdam, A. A., Nassar, S. M.: Automated vision system for localizing structural defects in textile fabrics. Pattern Recognition Letters 26(10), 1435-1443 (2005)
2. Bakker, T., Wouters, H., van Asselt, K., Bontsema, J., Tang, L., Muller, J., van Straten, G.: A vision based row detection system for sugar beet. Computers and Electronics in Agriculture 60(1), 87-95 (2008)
3. Chaira, T., Ray, A. K.: Threshold selection using fuzzy set theory. Pattern Recognition Letters 25(8), 865-874 (2004)
4. Chen, Y. R., Chao, K. L., Kim, M. S.: Machine vision technology for agricultural applications. Computers and Electronics in Agriculture 36(2-3), 173-191 (2002)
5. Funck, J. W., Zhong, Y., Butler, D. A., Brunner, C. C., Forrer, J. B.: Image segmentation algorithms applied to wood defect detection. Computers and Electronics in Agriculture 41(1-3), 157-179 (2003)
6. Zhang, H., Frittsb, J. E., Goldmana, S. A.: Image segmentation evaluation: A survey of unsupervised methods. Computer Vision and Image Understanding 110, 260-280 (2008)
7. Kim, B. G., Shim, J. I., Park, D. J.: Fast image segmentation based on multiresolution analysis and wavelets. Pattern Recognition Letters 24(6), 2995-3006 (2003)
8. Kwon, S. H.: Threshold selection based on cluster analysis. Pattern Recognition Letters 25(9), 1045-1050 (2004)
9. Lieberman, M. A., Bragg, C. K., Brennan, S. N.: Determining gravimetric bark content in cotton with machine vision. Textile Research Journal 68(2), 94-104 (1998)
10. Millman, M. P., Acar, M., Jackson, M. R.: Computer vision for textured yarn interlace (nip) measurements at high speeds. Mechatronics 11(8), 1025-1038 (2001)
11. Otsu, N.: A threshold selection method from gray-level histograms. IEEE Transactions on SMC 9(1), 62-66 (1979)
12. Pichel, J. C., Singh, D. E., Rivera, F. F.: Image segmentation based on merging of sub-optimal segmentations. Pattern Recognition Letters 27(10), 1105-1116 (2006)
13. Susomboon, R., Stan Raicu, D., Furst, J.: A hybrid approach for liver segmentation. In: MICCAI 2007 Workshop Proceedings of the 3D Segmentation in the Clinic: a Grand Challenge, pp. 151-160 (2007)
14. Su, Z. W., Tian, G. Y., Gao, C. H.: A machine vision system for on-line removal of contaminants in wool. Mechatronics 16(5), 243-247 (2006)
15. Yang, W., et al.: A new approach for image processing in foreign fiber detection. Comput. Electron. Agric. (2009), doi:10. 1016/j. compag. 2009. 04. 005
16. Zhang, H., Fritts, J. E., Goldman, S. A.: Image segmentation evaluation: a survey of unsupervised methods. Computer Vision and Image Understanding 110, 260-280 (2008)
17. Zhang, X., et al.: A Fast Segmentation Method for High-resolution Color Images of Cotton Foreign Fibers. Computers and Electronics in Agriculture (2011), doi:2011. 06. 005
18. Zhang, Y. J.: Image Engineering(II)Image Analysis. Tsinghua University Press, Beijing (2005)