Template-guided inspection of arbitrarily oriented targets

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Template-guided inspection of arbitrarily oriented targets

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The performance of template-based inspection of randomly oriented targets relies on the effective operation of two procedures: image registration and change detection. Each procedure is characterised by its own challenges. Real-time applications require that image registration is performed in an acceptable time with accurate results, regardless of structural distortions. Change detection can be hindered by noise fluctuations and illumination variations. An additional challenge in template-guided change detection comes from the fact that the decision needs to be based on a comparison restricted to two frames. The operation principles of a template-guided change detector are analysed. Image registration is based on a wavelet-based method which employs mutual information. A block-based change detection algorithm, which separates content alterations from noise-level fluctuations, illumination variations and shadows, is also analysed. The principles presented are combined for the implementation of a sample template-guided undervehicle surveillance system. The architecture of the system and its experimental results are presented, and practical aspects and considerations regarding the system design are discussed.

Inspec keywords: image registration; wavelet transforms; automatic optical inspection

Other keywords: image registration; noise fluctuation; block-based change detection algorithm; structural distortion; wavelet-based method; template-guided inspection; illumination variation; undervehicle surveillance system; randomly oriented target; content alteration; mutual information

Subjects: Computer vision and image processing techniques; Optical, image and video signal processing; Integral transforms; Integral transforms

References

    1. 1)
      • W.M. Wells , P. Viola , H. Atsumi , S. Nakajima , R. Kikinis . Multi-modal volume registration by maximization of mutual information. Med. Image Anal. , 1 , 35 - 51
    2. 2)
      • Baird, M.L.: `Image segmentation technique for locating automotive parts on belt conveyors', Int. Joint Conf. Artificial Intelligence, 1977, Cambridge, Massachusetts, USA, p. 694–695.
    3. 3)
      • A.M. Darwish , A.K. Jain . A rule based approach for visual pattern inspection. IEEE Trans. Pattern Anal. Mach. Intell. , 1 , 56 - 68
    4. 4)
      • L.G. Brown . A survey of image registration techniques. ACM Comput. Surv. (CSUR) , 4 , 325 - 376
    5. 5)
      • J. Le Moigne , W.J. Campbell , R.F. Cromp . An automated parallel image registration technique based on the correlation of wavelet features. IEEE Trans. Geosci. Remote Sens. , 8 , 1849 - 1864
    6. 6)
      • Harville, M., Gordon, G., Woodfill, J.: `Foreground segmentation using adaptive mixture models in color and depth', IEEE Workshop on Detection and Recognition of Events in Video, 8 July 2001, Vancouver, BC, Canada, p. 3–11.
    7. 7)
      • D.S. Lee . Effective Gaussian mixture learning for video background subtraction. IEEE Trans. Pattern Anal. Mach. Intell. , 5 , 827 - 832
    8. 8)
      • P. Viola , W.M. Wells . Alignment by maximization of mutual information. Int. J. Comput. Vis. , 2 , 137 - 154
    9. 9)
      • J.S. Walker . (1999) Wavelets and their scientific applications.
    10. 10)
      • F. Maes , A. Collignon , D. Vandermeulen , G. Marchal , P. Suetens . Multimodality image registration by maximization of mutual information. IEEE Trans. Med. Imaging , 2 , 187 - 198
    11. 11)
      • S.G. Mallat . A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans. Pattern Anal. Mach. Intell. , 7 , 674 - 693
    12. 12)
      • Modayur, B.R., Shapiro, L.G.: `Automated inspection of machine parts', 11thIAPR International Conf. Pattern Recognition, 30 August–3 September 1992, The Hague, Netherlands, 1, p. 57–60, Conference A: Computer Vision and Applications.
    13. 13)
      • B. Zitová , J. Flusser . Image registration methods: a survey. Image Vis. Comput. , 977 - 1000
    14. 14)
      • J.A. Noble , R. Gupta , J.L. Mundy , A. Schmitz , R.I. Hartley . High-precision X-ray stereo for automated 3-D CAD-based inspection. IEEE Trans. Robot. Autom. , 2 , 292 - 302
    15. 15)
      • M. Massey , W. Bender . Salient stills: process and practice. IBM Syst. J. , 557 - 573
    16. 16)
      • M. Moganti , F. Ercal , C.H. Dagli , S. Tsunekawa . Automatic PCB inspection algorithms: a survey. Comput. Vis. Image Underst. , 2 , 287 - 313
    17. 17)
      • R.J. Radke , S. Andra , O. Al-Kofahi , B. Roysam . Image change detection algorithms: a systematic survey. IEEE Trans. Image Process. , 3 , 294 - 307
    18. 18)
      • Toyama, K., Krumm, J., Brummit, B., Meyers, B.: `Wallflower: principles and practice of background maintenance', 7thIEEE Int. Conf. Computer Vision, 20–27 September 1999, Kerkyra, Greece, p. 255–261.
    19. 19)
      • M.S. Song . (2006) Wavelet image compression, Operator theory, operator algebras, and applications.
    20. 20)
      • Noble, A., Nguyen, V.D., Marinos, C.: `Template guided visual inspection', Proc. Second European Conf. Computer Vision, 1992, 588, p. 893–901, (Lecture Notes in Computer Science).
    21. 21)
      • Y.N. Sun , C.T. Tsai . New model-based approach for industrial visual inspection. Pattern Recognit. , 11 , 1327 - 1336
    22. 22)
      • Ridder, C., Munkelt, O., Kirchner, H.: `Adaptive background estimation and foreground detection using Kalman filtering', Int. Conf. Recent Advances in Mechatronics, 14 August 1995, Istanbul, Turkey, p. 193–199.
    23. 23)
      • Aach, T., Kaup, A., Mester, R.: `Change detection in image sequences using Gibbs random fields: a Bayesian approach', Int. Workshop on Intelligent Signal Processing and Communication Systems, 27–29 October 1993, Sendai, Japan, p. 56–61.
    24. 24)
      • A.A. Cole-Rhodes , K.L. Johnson , J. Le Moigne , I. Zavorin . Multiresolution registration of remote sensing imagery by optimization of mutual information using a stochastic gradient. IEEE Trans. Image Process. , 12 , 1495 - 1511
    25. 25)
      • A. Cavallaro , T. Ebrahimi . Video object extraction based on adaptive background and statistical change detection. Proc. SPIE, Vis. Commun. Image Process. , 465 - 475
    26. 26)
      • T. Aach , A. Kaup , R. Mester . Statistical model based change detection in moving video. Signal Process. , 2 , 165 - 180
    27. 27)
      • Stauffer, C., Grimson, W.E.L.: `Adaptive background mixture models for real-time tracking', IEEE Computer Society Conf. Computer Vision and Pattern Recognition, 23–25 June 1999, Fort Collins, Colorado, USA, 2, p. 246–252.
    28. 28)
      • Avnaim, F., Boissonnat, J.D.: `A geometric approach to inspection', 9thInt. Conf. Pattern Recognition, 14–17 November 1988, Rome, Italy, 2, p. 891–893.
    29. 29)
      • I. Haritaoglu , D. Harwood , L.S. Davis . W4: real-time surveillance of people and their activities. IEEE Trans.Pattern Anal. Mach. Intell. , 8 , 809 - 830
    30. 30)
      • El-Ghazawi, T.A., Chalermwat, P., Le Moigne, J.: `Wavelet based image registration on parallel computers', Proc. 1997 ACM/IEEE Conf. Supercomputing, 15–21 November 1997, San Jose, California, USA, p. 1–9.
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