Abstract
We have created an algorithm to integrate contour elements and find the salience value of them. The algorithm consists of basic long-range orientation specific neural connections as well as a novel group suppression gain control and a fast plasticity term to explain interaction beyond a neurons normal size range. Integration is executed as a series of convolutions on 12 orientation filtered images augmented by the nonlinear fast plasticity and group suppression terms. Testing done on a large number of artificially generated Gabor element contour images shows that the algorithm is effective at finding contour elements within parameters similar to that of human subjects. Testing of real world images yields reasonable results and shows that the algorithm has strong potential for use as an addition to our already existent vision saliency algorithm.
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© 2002 Springer-Verlag Berlin Heidelberg
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Mundhenk, T.N., Itti, L. (2002). A Model of Contour Integration in Early Visual Cortex. In: Bülthoff, H.H., Wallraven, C., Lee, SW., Poggio, T.A. (eds) Biologically Motivated Computer Vision. BMCV 2002. Lecture Notes in Computer Science, vol 2525. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36181-2_8
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DOI: https://doi.org/10.1007/3-540-36181-2_8
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