UND: unite-and-divide method in Fourier and Radon domains for line segment detection

SHI, Daming, GAO, Junbin, RAHMDEL, Payam S., ANTOLOVICH, Michael and CLARK, Tony (2013). UND: unite-and-divide method in Fourier and Radon domains for line segment detection. IEEE Transactions on Image Processing, 22 (6), 2501-2506.

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Abstract

Email Print Request Permissions In this paper, we extend our previously proposed line detection method to line segmentation using a so-called unite-and-divide (UND) approach. The methodology includes two phases, namely the union of spectra in the frequency domain, and the division of the sinogram in Radon space. In the union phase, given an image, its sinogram is obtained by parallel 2D multilayer Fourier transforms, Cartesian-to-polar mapping and 1D inverse Fourier transform. In the division phase, the edges of butterfly wings in the neighborhood of every sinogram peak are firstly specified, with each neighborhood area corresponding to a window in image space. By applying the separated sinogram of each such windowed image, we can extract the line segments. The division Phase identifies the edges of butterfly wings in the neighborhood of every sinogram peak such that each neighborhood area corresponds to a window in image space. Line segments are extracted by applying the separated sinogram of each windowed image. Our experiments are conducted on benchmark images and the results reveal that the UND method yields higher accuracy, has lower computational cost and is more robust to noise, compared to existing state-of-the-art methods.

Item Type:	Article
Research Institute, Centre or Group - Does NOT include content added after October 2018:	Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
Departments - Does NOT include content added after October 2018:	Faculty of Science, Technology and Arts > Department of Computing
Identification Number:	https://doi.org/10.1109/TIP.2013.2246522
Page Range:	2501-2506
Depositing User:	Tony Clark
Date Deposited:	20 Apr 2016 14:42
Last Modified:	18 Mar 2021 18:15
URI:	https://shura.shu.ac.uk/id/eprint/12034

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