Abstract
The problem of curve detection decomposes naturally into two stages: (i) inferring the (discrete) trace and tangent to the curve; and (ii) finding integrals through the resultant tangent field. Orientation selection is the term used by physiologists for the first of these stages; i.e., for the process of extracting the tangents to piecewise smooth curves from a two-dimensional image. We present an analysis of the orientation selection process from a computational perspective that is strongly influenced by various biological constraints. As such, it provides both a solid foundation for curve detection algorithms within computer vision systems and illustrates the insights that can be gained by analyzing biological vision systems. Formal extensions to the algorithm can also be posed that provide further insight into texture and optical flow.
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7. References
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© 1988 Springer-Verlag Berlin Heidelberg
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Zucker, S.W. (1988). A biologically motivated approach to early visual computations: orientation selection, texture, and optical flow. In: Kittler, J. (eds) Pattern Recognition. PAR 1988. Lecture Notes in Computer Science, vol 301. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-19036-8_42
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DOI: https://doi.org/10.1007/3-540-19036-8_42
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