Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering

Real-time Classified Hough Transform Line Detection Based on FPGA

Authors
Xinming Wang, Haishu Tan, Fuqiang Zhou, Yao Zhao
Corresponding Author
Xinming Wang
Available Online February 2016.
DOI
10.2991/iccsae-15.2016.101How to use a DOI?
Keywords
Line Detection; Gradient; Hough Transform; FPGA.
Abstract

Hough Transform (HT) is a popular tool for line detection due to its robustness to noise and missing data. This paper proposes a classified Hough Transform (CHT) to achieve real-time line detection on one kind of hardware circuit called FPGA. It makes full use of the gradient information calculated in the edge detection stage compared with other Hough Transforms. The results show that the proposed hardware algorithm is feasible. As the classified Hough Transform is divided into two independent parts according to gradient, every edge pixel is substituted into a single calculation formula, it accelerates computation with the same accuracy.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering
Series
Advances in Computer Science Research
Publication Date
February 2016
ISBN
10.2991/iccsae-15.2016.101
ISSN
2352-538X
DOI
10.2991/iccsae-15.2016.101How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xinming Wang
AU  - Haishu Tan
AU  - Fuqiang Zhou
AU  - Yao Zhao
PY  - 2016/02
DA  - 2016/02
TI  - Real-time Classified Hough Transform Line Detection Based on FPGA
BT  - Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering
PB  - Atlantis Press
SP  - 548
EP  - 554
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccsae-15.2016.101
DO  - 10.2991/iccsae-15.2016.101
ID  - Wang2016/02
ER  -