Please use this identifier to cite or link to this item:
https://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) |
Editor: | Jennane, R. |
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 |
DOI: | 10.1109/IPTA.2015.7367119 |
Published version: | http://dx.doi.org/10.1109/ipta.2015.7367119 |
Appears in Collections: | Aurora harvest 3 Computer Science publications |
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RA_hdl_107642.pdf Restricted Access | Restricted Access | 193.58 kB | Adobe PDF | View/Open |
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