Abstract
This article describes a neural architecture for real time preattentive segmentation of sewage pipes video images, whose mechanisms are based on the mammalian early visual system. The architecture corresponds to a modified and simplified version of the Boundary Contour System tuned to take advantage of the circular symmetric characteristics of the pipes images. Remarkable aspects of the proposed architecture are the application of a spatial complex logarithmic mapping stage, and the use of cooperative receptive fields with noncollinear branches.
The author is supported by a grant from the DAAD (Deutscher Akademischer Austauschdienst).
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Preattentive segmentation refers to the ability of mammalians to perceive textures without any sustained attention.
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© 1995 Springer-Verlag Berlin Heidelberg
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Ruiz-del-Solar, J., Köppen, M. (1995). A neural architecture for preattentive segmentation of sewage pipes video images. In: Mira, J., Sandoval, F. (eds) From Natural to Artificial Neural Computation. IWANN 1995. Lecture Notes in Computer Science, vol 930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-59497-3_262
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DOI: https://doi.org/10.1007/3-540-59497-3_262
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