Abstract
A computationally efficient implementation of the Hough transform, called the Adaptive Hough Transform is described. The method uses a coarse to fine search strategy to find peaks in the parameter space using a small accumulator array of fixed size. Its storage requirements are dramatically lower than those for the conventional Hough transform and it is also faster computationally when high dimensional parameter spaces are used. Shape detection using both natural representations of curves and hyperplane representations is discussed and the effectiveness of the method is demonstrated experimentally by applying it to the detection of parametric shapes in images of industrial objects.
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© 1988 Springer-Verlag Berlin Heidelberg
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Illingworth, J., Kittler, J., Princen, J. (1988). Shape Detection Using the Adaptive Hough Transform. In: Jain, A.K. (eds) Real-Time Object Measurement and Classification. NATO ASI Series, vol 42. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-83325-0_8
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DOI: https://doi.org/10.1007/978-3-642-83325-0_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-83327-4
Online ISBN: 978-3-642-83325-0
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