Improved Parallel Lane Detection Using Modified Additive Hough Transform

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Author(s)

Amandeep Katru 1,* Anil Kumar 1

1. Guru Nanak Dev University, Amritsar, 143001, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2016.11.02

Received: 14 Jul. 2016 / Revised: 24 Aug. 2016 / Accepted: 4 Oct. 2016 / Published: 8 Nov. 2016

Index Terms

Lane detection, Modified additive Hough transfom, parallelisms, dynamic thresholding

Abstract

Lane detection has recognition in real time vehicular ad-hoc system. That study work concentrate on giving greater efficiency in lane detection by utilizing the additive Hough transform to identify the curve lanes and convert into data parallelism in order to improve the speed of the proposed technique by using fork and join process. To accomplish performance evaluation various metrics is likely to be considered. The performance of lane detection algorithms is generally evaluated in terms of algorithm results and parallel results. Algorithm results is evaluated in terms of accuracy, error rate, execution time ,overhead and parallel results is evaluated in terms of speed, efficiency etc. To complete performance comparison the result of proposed algorithm is going to be compared with existing lane detection algorithms. Intelligent transportation systems are available these days for increasing the safety of the vehicles and reduce incident ratio. A new technique which uses modified additive hough transform is used to reduce the limitations of existing technique. The proposed algorithm has been designed and implemented in MATLAB. 

Cite This Paper

Amandeep Katru, Anil Kumar,"Improved Parallel Lane Detection Using Modified Additive Hough Transform", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.8, No.11, pp.10-17, 2016. DOI: 10.5815/ijigsp.2016.11.02

Reference

[1]Yi, Shu-Chung, Yeong-Chin Chen, and Ching-Haur Chang. "A lane detection approach based on intelligent vision." Computers & Electrical Engineering 42 ,23-29 (2015).

[2]Huachun Tan; Yang Zhou; Yong Zhu; Danya Yao; Keqiang Li, "A novel curve lane detection based on Improved River Flow and RANSA," in Intelligent Transportation Systems (ITSC), 2014 IEEE 17th International Conference on , vol., no., pp.133-138, 8-11 Oct. 2014.

[3]A. Filonenko, D. C. Hernández, L. Kurnianggoro, D. Seo and K. H. Jo, "Real-time lane marking detection," Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on, Gdynia, 2015, pp. 125-128.

[4]Heechul Jung; Junggon Min; Junmo Kim, "An efficient lane detection algorithm for lane departure detection," in Intelligent Vehicles Symposium (IV), 2013 IEEE , vol., no., pp.976-981, 23-26 June 2013.

[5]F. Bounini, D. Gingras, V. Lapointe and H. Pollart, "Autonomous Vehicle and Real Time Road Lanes Detection and Tracking," Vehicle Power and Propulsion Conference (VPPC), 2015 IEEE, Montreal, QC, 2015, pp. 1-6.

[6]J. S. Kang, J. Kim and M. Lee, "Advanced driver assistant system based on monocular camera," 2014 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, 2014, pp. 55-56.

[7]Zezhi Chen; Ellis, T., "Automatic lane detection from vehicle motion trajectories," in Advanced Video and Signal Based Surveillance (AVSS), 2013 10th IEEE International Conference on , vol., no., pp.466-471, 27-30 Aug. 2013.

[8]Ju Han, Yoo Dong, Hwan Kim and Sung-Kee Park, "A new lane detection method based on vanishing point estimation with probabilistic voting," 2015 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, 2015, pp. 204-205.

[9]Jae-Hyun Cho; Tsogtbaatar, E.; Seong-Hoon Kim; Young-Min Jang; Pham-Minh-Luan Nguyen; Sang-Bock Cho, "Improved lane detection system using Hough transform with super-resolution reconstruction algorithm and multi-ROI," in Electronics, Information and Communications (ICEIC), 2014 International Conference on , vol., no., pp.1-4, 15-18 Jan. 2014.

[10]Seung-Nam Kang; Soomok Lee; Junhwa Hur; Seung-Woo Seo, "Multi-lane detection based on accurate geometric lane estimation in highway scenarios," in Intelligent Vehicles Symposium Proceedings, 2014 IEEE , vol., no., pp.221-226, 8-11 June 2014.

[11]Jianyu Yang; Zhuo Li; Liangchao Li, "Lan detection based on classification of lane geometrical model," in Signal Processing (ICSP), 2012 IEEE 11th International Conference on , vol.2, no., pp.842-846, 21-25 Oct. 2012.

[12]Baykal, B.; Ozcan, A.R.; Erturk, S., "Lane detection system based on one bit transform," in Signal Processing and Communications Applications Conference (SIU), 2014 22nd , vol., no., pp.2237-2240, 23-25 April 2014.

[13]Tao Tan, Shouyi Yin, Peng Ouyang, Leibo Liu and Shaojun Wei, "Efficient lane detection system based on monocular camera," 2015 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, 2015, pp. 202-203.

[14]Deusch, H.; Wiest, J.; Reuter, S.; Szczot, M.; Konrad, M.; Dietmayer, K., "A random finite set approach to multiple lane detection," in Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on , vol., no., pp.270-275, 16-19 Sept. 2012

[15]Hunjae Yoo; Ukil Yang; Kwanghoon Sohn, "Gradient-Enhancing Conversion for Illumination-Robust Lane Detection," in Intelligent Transportation Systems, IEEE Transactions on , vol.14, no.3, pp.1083-1094, Sept. 2013.

[16]Braga de Paula, M.; Rosito Jung, C., "Real-Time Detection and Classification of Road Lane Markings," in Graphics, Patterns and Images (SIBGRAPI), 2013 26th SIBGRAPI - Conference on , vol., no., pp.83-90, 5-8 Aug. 2013.

[17]Jun Wang; Tao Mei; Bin Kong; Hu Wei, "An approach of lane detection based on Inverse Perspective Mapping," in Intelligent Transportation Systems (ITSC), 2014 IEEE 17th International Conference on , vol., no., pp.35-38, 8-11 Oct. 2014.

[18]R. Gopalan, T. Hong, M. Shneier and R. Chellappa, "A Learning Approach Towards Detection and Tracking of Lane Markings," in IEEE Transactions on Intelligent Transportation Systems, vol. 13, no. 3, pp. 1088-1098, Sept. 2012.

[19]X. Li, Q. Wu, Y. Kou, L. Hou and H. Yang, "Lane detection based on spiking neural network and hough transform," 2015 8th International Congress on Image and Signal Processing (CISP), Shenyang, 2015, pp. 626-630. 

[20]Chien Tsung-Yu; Chung Sheng-Luen, "Android-based driving assistant for lane detection and departure warning," in Control Conference (CCC), 2014 33rd Chinese , vol., no., pp.174-179,28-30July2014.