IEEE Trans Image Process - Accurate and robust line segment extraction using minimum entropy with Hough transform.

Tópicos

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Resumo

The Hough transform is a popular technique used in the field of image processing and computer vision. With a Hough transform technique, not only the normal angle and distance of a line but also the line-segment's length and midpoint (centroid) can be extracted by analysing the voting distribution around a peak in the Hough space. In this paper, a method based on minimum-entropy analysis is proposed to extract the set of parameters of a line segment. In each column around a peak in Hough space, the voting values specify probabilistic distributions. The corresponding entropies and statistical means are computed. The line-segment's normal angle and length are simultaneously computed by fitting a quadratic polynomial curve to the voting entropies. The line-segment's midpoint and normal distance are computed by fitting and interpolating a linear curve to the voting means. The proposed method is tested on simulated images for detection accuracy by providing comparative results. Experimental results on real-world images verify the method as well. The proposed method for line-segment detection is both accurate and robust in the presence of quantization error, background noise, or pixel disturbances.

Resumo Limpo

hough transform popular techniqu use field imag process comput vision hough transform techniqu normal angl distanc line also lineseg length midpoint centroid can extract analys vote distribut around peak hough space paper method base minimumentropi analysi propos extract set paramet line segment column around peak hough space vote valu specifi probabilist distribut correspond entropi statist mean comput lineseg normal angl length simultan comput fit quadrat polynomi curv vote entropi lineseg midpoint normal distanc comput fit interpol linear curv vote mean propos method test simul imag detect accuraci provid compar result experiment result realworld imag verifi method well propos method lineseg detect accur robust presenc quantiz error background nois pixel disturb

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