Abstract
Target recognition is the ability to find and delineate objects within an image. This is not an easy task for most applications. The targets can be presented in a variety of different views, rotations, scales, illumination, etc. Traditional target recognition methods have been successful only in limited cases and views. However, the three basic steps to Automatic Target Recognition or ATR are well known: (i) segment the image into regions, (ii) determine features in the image regions, and (iii) classify the regions by their features. Living creatures do this ail the time. Flies do it. Fish do it. Spiders do it, even little spiders. Yet it is still eluding researchers.
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References
J. W. Goodman, Introduction to Fourier Optics, McGrawHill, (1968).
John L. Johnson, Mary Lou Padgett and William A. Friday Multiscale Image Factorisation, Proceedings of the International Conference on Neural Networks, ICNN97, Houston TX, June, 1997, Invited paper, pp. 1465–1468.
H. Niemann, Pattern Analysis and Understanding, Springer-Verlag (1981).
Mary Lou Padgett and John L. Johnson, Pulse-Coupled Neural Networks (PCNN) and Wavelets: Biosensor Applications, Proceedings of the International Conference on Neural Networks, ICNN97, Houston TX, June, 1997, Invited paper, pp. 2507–2512.
D. K. Pollack, C. J. Koester, J. T. Tippett, Eds. Optical Processing and Information, Spartan Books, Baltimore, MD (1963).
F. T. S. Yu, Optical Information Processing; Optical Signal Processing, Fourier Optics, John Wiley & Sons, (1983).
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© 1998 Springer-Verlag London
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Lindblad, T., Kinser, J.M. (1998). Target Recognition. In: Image Processing using Pulse-Coupled Neural Networks. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-3617-0_5
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DOI: https://doi.org/10.1007/978-1-4471-3617-0_5
Publisher Name: Springer, London
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