2008
DOI: 10.1016/j.patcog.2007.04.003
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Real-time line detection through an improved Hough transform voting scheme

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Cited by 378 publications
(197 citation statements)
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“…Since the NOvA data is composed of a two-dimensional image for each view, this makes the Hough transform an ideal algorithm as a first step to finding the global event features and the vertex. The method described 115 below is based off of a modified, two-point Hough transform originally outlined in [67].…”
Section: The Multi-hough Transformmentioning
confidence: 99%
“…Since the NOvA data is composed of a two-dimensional image for each view, this makes the Hough transform an ideal algorithm as a first step to finding the global event features and the vertex. The method described 115 below is based off of a modified, two-point Hough transform originally outlined in [67].…”
Section: The Multi-hough Transformmentioning
confidence: 99%
“…Our software was implemented in C++ using Minpack [17] optimization library and KHT Sandbox (https://sourceforge.net/projects/khtsandbox) [18], the reference implementation of the kernel-based Hough transform for detecting straight lines in binary images. It allows a software implementation to achieve real-time performance even on relatively large images.…”
Section: Experiments and Autogenerated Modelsmentioning
confidence: 99%
“…The major drawback of the HT is the multiple response of a line and detection of infinite lines on edge map with one pixel width, which makes it unsuitable for power line detection (Fernandes & Oliveira, 2008). Inspired by (Von Gioi, et al, 2010), the idea of region growing and connected component analysis are adopted in this paper.…”
Section: Line Feature Extractionmentioning
confidence: 99%
“…Most of the recently proposed methods are based on either gradient/edge (Akinlar & Topal, 2011;Fernandes & Oliveira, 2008;Nieto, et al, 2011;Von Gioi, et al, 2010) or ridge/valley information (Jang & Hong, 2002;Koller, et al, 1995;Steger, 1998). Another well known approach is the Hough transform (Hough, 1962).…”
Section: Introductionmentioning
confidence: 99%
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