Abstract
The traditional approach in detecting sets of concurrent and/or parallel lines is to first detect lines in the image and then find such groups of them which meet the concurrence condition. The Hough Transform can be used for detecting the lines and variants of HT such as the Cascaded Hough Transform can be used to detect the vanishing points. However, these approaches disregard much of the information actually accumulated to the Hough space. This article proposes using the Hough space as a 2D signal instead of just detecting the local maxima and processing them. On the example of QRcode detection, it is shown that this approach is computationally cheap, robust, and accurate. The proposed algorithm can be used for efficient and accurate detection and localization of matrix codes (QRcode, Aztec, DataMatrix, etc.) and chessboard-like calibration patterns.
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Notes
Downloadable from http://medusa.fit.vutbr.cz/pclines/.
Downloadable from http://medusa.fit.vutbr.cz/pclines/.
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Acknowledgments
This research was supported by the CEZMSMT project IT4I—CZ 1.05/1.1.00/02.0070, by the TACR grant V3C TE01010415 and by MV CR grant VG20102015006.
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Dubská, M., Herout, A. & Havel, J. Real-time precise detection of regular grids and matrix codes. J Real-Time Image Proc 11, 193–200 (2016). https://doi.org/10.1007/s11554-013-0325-6
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DOI: https://doi.org/10.1007/s11554-013-0325-6