Multidimensional lines I: representation
SIAM Journal on Applied Mathematics
Multidimensional lines II: proximity and applications
SIAM Journal on Applied Mathematics
An Active Testing Model for Tracking Roads in Satellite Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
A Robust Software Barcode Reader Using the Hough Transform
ICIIS '99 Proceedings of the 1999 International Conference on Information Intelligence and Systems
Accuracy of the straight line Hough transform: the non-voting approach
Computer Vision and Image Understanding
Extracting Lines in Noisy Image Using Directional Information
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Extended Hough transform for linear feature detection
Pattern Recognition
Advanced hough transform using a multilayer fractional fourier method
IEEE Transactions on Image Processing
Advanced Radon transform using generalized interpolated Fourier method for straight line detection
Computer Vision and Image Understanding
Ridges and valleys detection in images using difference of rotating half smoothing filters
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Vanishing points in point-to-line mappings and other line parameterizations
Pattern Recognition Letters
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Straight-line detection is important in several fields such as robotics, remote sensing, and imagery. The objective of this paper is to present several methods, old and new, used for straight-line detection. We begin by reviewing the standard Hough transform (SHT), then three new methods are suggested: the revisited Hough transform (RHT), the parallel-axis transform (PAT), and the circle transform (CT). These transforms utilize a point-line duality to detect straight lines in an image. The RHT and the PAT should be faster than the SHT and the CT because they use line segments whereas the SHT uses sinusoids and CT uses circles. Moreover, the PAT, RHT, and CT use additions and multiplications whereas the SHT uses trigonometric functions (sine and cosine) for calculation. To compare the methods we analyze the distribution of the frequencies in the accumulators and observe the effect on the detection of false local maxima. We also compare the robustness to noise of the four transforms. Finally, an example with a real image is given.