Connective Randomized Hough Transform (crht)
نویسندگان
چکیده
A new branch of Hough Transform algorithms, called probabilistic Hough Transforms, has been actively developed in recent years. One of the rst was a new and eecient probabilistic version of the Hough Transform for curve detection, the Randomized Hough Transform (RHT). The RHT picks n pixels from an edge image by random sampling to solve n parameters of a curve and then accumulates only one cell in a parameter space. In this paper, a novel extension of the RHT, called the Connective Randomized Hough Transform (CRHT), is suggested to improve the RHT for complex and noisy pictures. Tests with synthetic and real-world images verify the high speed and low memory usage of the CRHT, as compared both to the Standard Hough Transform and the basic RHT.
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