Abstract
This paper considers the problem of detecting lines in images using a pyramid architecture. The approach is based on the Hough Transform calculation. A pyramid architecture of size n is a fine-grain architecture with a mesh base of size [Formula: see text] processors each holding a single pixel of the image. The pyramid operates in an SIMD mode. Two algorithms for computing the Hough Transform are explained. The first algorithm initially uses different angles, θj’s, and its complexity is O(k+log n) with O(m) storage requirement. The second algorithm computes the Hough Transform in a pipeline fashion for each angle θj at a time. This method produces results in O(k * log n) time with O(1) storage, where k is the number of θj angles, m is the number of ρi normal distances from the origin, and n is the number of pixels. A simulation program is also described.
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More From: International Journal of Pattern Recognition and Artificial Intelligence
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