Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/107642
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Type: Conference paper
Title: Theoretical analysis of hough transform optimal cell size: Segmentation of nearby lines
Author: Hadian-Jazi, M.
Bab-Hadiashar, A.
Hoseinnezhad, R.
Suter, D.
Citation: Image Processing, Theory, Tools and Applications, 2015 / Jennane, R. (ed./s), pp.163-168
Publisher: IEEE
Issue Date: 2015
Series/Report no.: International Conference on Image Processing Theory Tools and Applications
ISBN: 9781479986354
ISSN: 2154-512X
Conference Name: IEEE International Conference on Image Processing Theory, Tools and Applications (IPTA) (10 Nov 2015 - 13 Nov 2015 : Orleans, France)
Statement of
Responsibility: 
Marjan Hadian-Jazi, Alireza Bab-Hadiashar, Reza Hoseinnezhad, and David Suter
Abstract: Hough Transform (HT) is commonly used to solve the line extraction problem. Although images are discretized at the onset, the Hough domain is continuous and in practice it has to be partitioned into cells. It has been suggested that the optimality of the size (resolution) of those cells would depend on the amount noise in the image. In this paper, we study the effect of discretization on the success of line detection where there are nearby lines and develop a theoretical foundation for the optimality of the Hough domain discretization for segmentation purposes. Experiments with real images show that our results are useful in practice for line detection applications.
Keywords: Line detection; Hough Transform; Cell Size
Rights: © 2015 IEEE
RMID: 0030046978
DOI: 10.1109/IPTA.2015.7367119
Appears in Collections:Computer Science publications

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