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Volumn 39, Issue 9, 2006, Pages 1679-1694

An independent component analysis-based filter design for defect detection in low-contrast surface images

Author keywords

Convolution filter; Defect detection; Independent component analysis; Particle swarm optimization; Surface inspection

Indexed keywords

COMPUTATION THEORY; CONVOLUTION; DEFECTS; DIGITAL FILTERS; IMAGE ANALYSIS; LIQUID CRYSTAL DISPLAYS; OPTIMIZATION;

EID: 33745047543     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2006.03.005     Document Type: Article
Times cited : (92)

References (44)
  • 1
    • 0002438592 scopus 로고
    • Finding and evaluating defects in glass
    • Freeman H. (Ed), Academic Press, New York, NY
    • Wilder J. Finding and evaluating defects in glass. In: Freeman H. (Ed). Machine Vision for Inspection and Measurement (1989), Academic Press, New York, NY 237
    • (1989) Machine Vision for Inspection and Measurement , pp. 237
    • Wilder, J.1
  • 2
    • 33745028007 scopus 로고    scopus 로고
    • J. Olsson, S. Gruber, Web process inspection using neural classification of scattering light, Proceedings of the IEEE International Conference on Industrial Electronics, Control, Instrumentation and Automation (IECON'92), 1992, pp. 1443-1448.
  • 3
    • 33745047187 scopus 로고    scopus 로고
    • C. Fernandez, D. Platero, P. Campoy, R. Aracil, Vision system for on-line surface inspection in aluminum casting process, Proceedings of the IEEE International Conference on Industrial Electronics, Control, Instrumentation and Automation (IECON'93), 1993, pp. 1854-1859.
  • 4
    • 0030211309 scopus 로고    scopus 로고
    • Designing defect classification system: a case study
    • Brzakovic D., and Vujovic N. Designing defect classification system: a case study. Pattern Recognition 29 (1996) 1401-1419
    • (1996) Pattern Recognition , vol.29 , pp. 1401-1419
    • Brzakovic, D.1    Vujovic, N.2
  • 5
    • 0030244413 scopus 로고    scopus 로고
    • Statistical methods to compare the texture features of machine surfaces
    • Ramana K.V., and Ramamoorthy B. Statistical methods to compare the texture features of machine surfaces. Pattern Recognition 29 (1996) 1447-1459
    • (1996) Pattern Recognition , vol.29 , pp. 1447-1459
    • Ramana, K.V.1    Ramamoorthy, B.2
  • 6
    • 8644232477 scopus 로고    scopus 로고
    • Detection of spot-type defects on liquid crystal display modules
    • Kim W.-S., Kwak D.-M., Song Y.-C., Choi D.-H., and Park K.-H. Detection of spot-type defects on liquid crystal display modules. Key Eng. Mater. 270-273 (2004) 808-813
    • (2004) Key Eng. Mater. , vol.270-273 , pp. 808-813
    • Kim, W.-S.1    Kwak, D.-M.2    Song, Y.-C.3    Choi, D.-H.4    Park, K.-H.5
  • 7
    • 0033336322 scopus 로고    scopus 로고
    • F. Saitoh, Boundary extraction of brightness unevenness on LCD display using genetic algorithm based on perceptive grouping factors, Proceedings of the International Conference on Image Processing, Kobe, Japan, 1999, pp. 308-312.
  • 8
    • 27844501085 scopus 로고    scopus 로고
    • Liquid crystal display surface uniformity defect inspection using analysis of variance and exponentially weighted moving average techniques
    • Jiang B.C., Wang C.-C., and Liu H.-C. Liquid crystal display surface uniformity defect inspection using analysis of variance and exponentially weighted moving average techniques. Int. J. Prod. Res. 43 (2005) 67-80
    • (2005) Int. J. Prod. Res. , vol.43 , pp. 67-80
    • Jiang, B.C.1    Wang, C.-C.2    Liu, H.-C.3
  • 9
    • 0026971015 scopus 로고    scopus 로고
    • S.M. Sokolov, A.S. Treskunov, Automatic vision system for final test of liquid crystal display, Proceedings of the IEEE International Conference on Robotics and Automation, Nice, France, 1992, pp. 1578-1582.
  • 10
    • 7544230477 scopus 로고    scopus 로고
    • Automatic detection of region-mura defect in TFT-LCD
    • Lee J.Y., and Yoo S.I. Automatic detection of region-mura defect in TFT-LCD. IEICE Trans. Inf. Syst. E87-D (2004) 2371-2378
    • (2004) IEICE Trans. Inf. Syst. , vol.E87-D , pp. 2371-2378
    • Lee, J.Y.1    Yoo, S.I.2
  • 13
    • 0034551787 scopus 로고    scopus 로고
    • Independent component analysis for noisy data-MEG data analysis
    • Ikeda S., and Toyama K. Independent component analysis for noisy data-MEG data analysis. Neural Networks 13 (2000) 1063-1074
    • (2000) Neural Networks , vol.13 , pp. 1063-1074
    • Ikeda, S.1    Toyama, K.2
  • 16
    • 0042819875 scopus 로고    scopus 로고
    • Temporally constrained ICA: an application to artifact rejection in electromagnetic brain signal analysis
    • James C.J., and Gibson O.J. Temporally constrained ICA: an application to artifact rejection in electromagnetic brain signal analysis. IEEE Trans. Biomed. Eng. 50 (2003) 1108-1116
    • (2003) IEEE Trans. Biomed. Eng. , vol.50 , pp. 1108-1116
    • James, C.J.1    Gibson, O.J.2
  • 17
    • 1342324773 scopus 로고    scopus 로고
    • Probabilistic independent component analysis for functional magnetic resonance imaging
    • Beckmann C.F., and Smith S.M. Probabilistic independent component analysis for functional magnetic resonance imaging. IEEE Trans. Med. Imaging 23 (2004) 137-152
    • (2004) IEEE Trans. Med. Imaging , vol.23 , pp. 137-152
    • Beckmann, C.F.1    Smith, S.M.2
  • 18
    • 0030262312 scopus 로고    scopus 로고
    • Application of blind source separation techniques to multi-tag contactless identification systems
    • Deville Y., and Andry L. Application of blind source separation techniques to multi-tag contactless identification systems. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. E79-A (1996) 1694-1699
    • (1996) IEICE Trans. Fundam. Electron. Commun. Comput. Sci. , vol.E79-A , pp. 1694-1699
    • Deville, Y.1    Andry, L.2
  • 19
    • 0033343361 scopus 로고    scopus 로고
    • On subband-based blind signal separation for noisy speech recognition
    • Park H.M., Jung H.Y., Lee T.W., and Lee S.Y. On subband-based blind signal separation for noisy speech recognition. Electron. Lett. 35 (1999) 2011-2012
    • (1999) Electron. Lett. , vol.35 , pp. 2011-2012
    • Park, H.M.1    Jung, H.Y.2    Lee, T.W.3    Lee, S.Y.4
  • 21
    • 0036604858 scopus 로고    scopus 로고
    • Face representation using independent component analysis
    • Yuen P.C., and Lai J.H. Face representation using independent component analysis. Pattern Recognition 35 (2002) 1247-1257
    • (2002) Pattern Recognition , vol.35 , pp. 1247-1257
    • Yuen, P.C.1    Lai, J.H.2
  • 22
    • 17144441960 scopus 로고    scopus 로고
    • Face recognition using independent component analysis and support vector machines
    • Deniz O., Castrillon M., and Hernandez M. Face recognition using independent component analysis and support vector machines. Pattern Recognition Lett. 24 (2003) 2153-2157
    • (2003) Pattern Recognition Lett. , vol.24 , pp. 2153-2157
    • Deniz, O.1    Castrillon, M.2    Hernandez, M.3
  • 23
    • 3042590909 scopus 로고    scopus 로고
    • Independent component analysis in a local facial residue space for face recognition
    • Kim T.K., Kim H., Hwang W., and Kittler J. Independent component analysis in a local facial residue space for face recognition. Pattern Recognition 37 (2004) 1873-1885
    • (2004) Pattern Recognition , vol.37 , pp. 1873-1885
    • Kim, T.K.1    Kim, H.2    Hwang, W.3    Kittler, J.4
  • 24
    • 85139272424 scopus 로고    scopus 로고
    • R. Manduchi, J. Portilla, Independent component analysis of textures, Proceedings of the IEEE International Conference on Computer Vision, Kerkyra, Greece, 1999, pp. 1054-1060.
  • 25
    • 33751561746 scopus 로고    scopus 로고
    • Y.W. Chen, X.Y. Zeng, H. Lu, Edge detection and texture segmentation based on independent component analysis, Proceedings of the 16th International Conference on Pattern Recognition, Quebec City, Canada, 2002, pp. 351-354.
  • 26
    • 0041698403 scopus 로고    scopus 로고
    • Independent component analysis for texture segmentation
    • Jenssen R., and Eltoft T. Independent component analysis for texture segmentation. Pattern Recognition 36 (2003) 2301-2315
    • (2003) Pattern Recognition , vol.36 , pp. 2301-2315
    • Jenssen, R.1    Eltoft, T.2
  • 27
    • 0031643603 scopus 로고    scopus 로고
    • A. Hyvarinen, P. Hoyer, E. Oja, Sparse code shrinkage for image denoising, Proceedings of the IEEE International Joint Conference on Neural Networks, Ahchorage, Alaska, 1998, pp. 859-864.
  • 28
    • 0003218917 scopus 로고    scopus 로고
    • Image denoising by sparse code shrinkage
    • Haykin S., and Kosko B. (Eds), IEEE Press, New York, NY
    • Hyvarinen A., Hoyer P., and Oja E. Image denoising by sparse code shrinkage. In: Haykin S., and Kosko B. (Eds). Intelligent Signal Processing (2001), IEEE Press, New York, NY 554-568
    • (2001) Intelligent Signal Processing , pp. 554-568
    • Hyvarinen, A.1    Hoyer, P.2    Oja, E.3
  • 29
    • 0348223982 scopus 로고    scopus 로고
    • Sparse code shrinkage: denoising of nongaussian data by maximum likelihood estimation
    • Hyvarinen A. Sparse code shrinkage: denoising of nongaussian data by maximum likelihood estimation. Neural Comput. 11 (1999) 1739-1768
    • (1999) Neural Comput. , vol.11 , pp. 1739-1768
    • Hyvarinen, A.1
  • 30
    • 84949237031 scopus 로고    scopus 로고
    • Y. Hung, S. Luo, A dynamic denoising natural image compression, Proceedings of the International Conference on Signal Processing, Beijing, China, 2002, pp. 1179-1182.
  • 31
    • 0042826822 scopus 로고    scopus 로고
    • Independent component analysis: algorithms and applications
    • Hyvarinen A., and Oja E. Independent component analysis: algorithms and applications. Neural Networks 13 (2000) 411-430
    • (2000) Neural Networks , vol.13 , pp. 411-430
    • Hyvarinen, A.1    Oja, E.2
  • 32
    • 0029411030 scopus 로고
    • An information-maximization approach to blind separation and blind deconvolution
    • Bell A.J., and Sejnowski T.J. An information-maximization approach to blind separation and blind deconvolution. Neural Comput. 7 (1995) 1129-1159
    • (1995) Neural Comput. , vol.7 , pp. 1129-1159
    • Bell, A.J.1    Sejnowski, T.J.2
  • 33
    • 33749754615 scopus 로고    scopus 로고
    • A new learning algorithm for blind source separation
    • Touretzky D., Mozer M., and Hasselmo M. (Eds), MIT Press, Cambridge, MA
    • Amari A., Cichocki A., and Yang H. A new learning algorithm for blind source separation. In: Touretzky D., Mozer M., and Hasselmo M. (Eds). Advances in Neural Information Processing Systems (1996), MIT Press, Cambridge, MA 757-763
    • (1996) Advances in Neural Information Processing Systems , pp. 757-763
    • Amari, A.1    Cichocki, A.2    Yang, H.3
  • 34
    • 0346307721 scopus 로고    scopus 로고
    • A fast fixed-point algorithm for independent component analysis
    • Hyvarinen A., and Oja E. A fast fixed-point algorithm for independent component analysis. Neural Comput. 9 (1997) 1483-1492
    • (1997) Neural Comput. , vol.9 , pp. 1483-1492
    • Hyvarinen, A.1    Oja, E.2
  • 35
    • 0032629347 scopus 로고    scopus 로고
    • Fast and robust fixed-point algorithms for independent component analysis
    • Hyvarinen A. Fast and robust fixed-point algorithms for independent component analysis. IEEE Trans. Neural Networks 10 (1999) 626-634
    • (1999) IEEE Trans. Neural Networks , vol.10 , pp. 626-634
    • Hyvarinen, A.1
  • 36
    • 0029535737 scopus 로고    scopus 로고
    • J. Kennedy, R. Eberhart, Particle swarm optimization, Proceedings of the IEEE International Conference on Neural Networks, Perth, Australia, 1995, pp. 1942-1948.
  • 37
    • 0034430526 scopus 로고    scopus 로고
    • A particle swarm optimization for reactive power and voltage control considering voltage security assessment
    • Yoshida H., Kawata K., Fukuyama Y., Takayama S., and Nakanishi Y. A particle swarm optimization for reactive power and voltage control considering voltage security assessment. IEEE Power Syst. 15 (2000) 1232-1239
    • (2000) IEEE Power Syst. , vol.15 , pp. 1232-1239
    • Yoshida, H.1    Kawata, K.2    Fukuyama, Y.3    Takayama, S.4    Nakanishi, Y.5
  • 39
    • 0036079715 scopus 로고    scopus 로고
    • R. Mendes, P. Cortez, M. Rocha, J. Neves, Particle swarms for feedforward neural network training, Proceedings of the International Joint Conference on Neural Networks, Honolulu, Hawaii, 2002, pp. 1895-1899.
  • 40
    • 0042526087 scopus 로고    scopus 로고
    • Particle swarm optimization to solving the economic dispatch considering the generator constraints
    • Gaing Z.-L. Particle swarm optimization to solving the economic dispatch considering the generator constraints. IEEE Trans. Power Syst. 18 (2003) 1187-1195
    • (2003) IEEE Trans. Power Syst. , vol.18 , pp. 1187-1195
    • Gaing, Z.-L.1
  • 41
    • 0031700696 scopus 로고    scopus 로고
    • Y. Shi, R. Eberhart, A modified particle swarm optimizer, Proceedings of the IEEE International Conference on Evolutionary Computation, Anchorage, Alaska, 1998, pp. 69-73.
  • 42
    • 0030645460 scopus 로고    scopus 로고
    • J. Kennedy, The particle swarm: social adaptation of knowledge, Proceedings of the IEEE International Conference on Evolutionary Computation, Piscataway, NJ, 1997, pp. 303-308.
  • 44
    • 33745045805 scopus 로고    scopus 로고
    • An adaptive Wiener filter based technique for automated detection of defect locations from bobbin coil eddy current data
    • Das M., Ramuhalli P., Udpa L., and Udpa S. An adaptive Wiener filter based technique for automated detection of defect locations from bobbin coil eddy current data. AIP (American Institute of Physics) Conf. Proc. 615 (2002) 639-646
    • (2002) AIP (American Institute of Physics) Conf. Proc. , vol.615 , pp. 639-646
    • Das, M.1    Ramuhalli, P.2    Udpa, L.3    Udpa, S.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.