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- W2185446043 abstract "The purpose of this contribution is to analyze the computational complexity of the Generalized Hough Transform (GHT) on a meshconnected computer (MCC) and to produce a practical algorithm for bi-dimensional shape recognition which is useful in any real situation, not just in the asymptotic case. In the following, the problem of shape detection shall be briefly introduced, along with a description of the Generalized Hough Transform. It will be shown how to map such a transform on a massively parallel computer that consists of a mesh of 4-connected processing elements (PE's). The mapping uses formally defined, general purpose data movements techniques that have been introduced for other kinds of problems on such architectures. Using these results, it is shown that the time complexity of the GHT is O(Rnlogn), being R the number of points used to describe the shape and n the linear dimension of the MCC. Even if theoretically important, such asymptotic complexity has few practical bearing; the associated constant is quite large. Moreover, using such data movements, one cannot apply an important criterion that drives the application of the GHT: the locality of the transform with respect to input image. Indeed, most shapes are bound by a circle having a radius d usually much smaller than the linear dimension of the mesh. Taking into account this geomemc constraint, one can design an improved algorithm whose time complexity O(Rd210gn) compares well, for practical situations, with that of the standard algorithms. Shape detection and the Generalized Hough Transform" @default.
- W2185446043 created "2016-06-24" @default.
- W2185446043 creator A5086275106 @default.
- W2185446043 date "1991-01-01" @default.
- W2185446043 modified "2023-09-26" @default.
- W2185446043 title "MAPPING THE GENERALIZED HOUGH TRANSFORM ON A MESH CONNECTED COMPUTER" @default.
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