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A Hybrid Method for Road Marking Detection

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Very recently, the problems posed in the context of road safety have taken off with the growing number of accidents on the roads. These accidents result in property damage and death in several cases. Nowadays, it is no longer a question of settling for a simple conventional and ordinary road safety, but an automatic road safety is widely desired. This study fits precisely into this context and proposes, first and in terms of computer vision, a combination of two types of approaches, which are by appearance and structural. Indeed the appearance approach is presented by the statistical classifier, while the structural one is given by the set of the following methods: the detection of the segments using the algorithm of the semi local analysis, the combined Kalman filter with predictor to estimate the road line, and the layout adjustment by applying the principle of Minimum Mean Square Error (MMSE). This method is tested on several sample images and videos. It has given a good quality results with very short processing times.
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Road Safety; Computer Vision; Road Marking; Detection; Appearance Approach; Structural Approach

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Daghouj, D., Abdellaoui, M., Fattah, M., Mazer, S., Balboul, Y., El Bekkali, M., Automatic Target Recognition Based on the Features of UWB Radar Signals, (2021) International Journal on Engineering Applications (IREA), 9 (6), pp. 310-316.

Ourabah, L., El Kari, B., Labriji, E., Fuzzy Graph-Based Controller for a Real-Time Urban Traffic Optimization, (2020) International Review on Modelling and Simulations (IREMOS), 13 (5), pp. 354-361.

Alhasanat, M., Alsafasfeh, M., Alhasanat, A., Althunibat, S., RetinaNet-Based Approach for Object Detection and Distance Estimation in an Image, (2021) International Journal on Communications Antenna and Propagation (IRECAP), 11 (1), pp. 19-25.

Michal Mandlik, Vladimir Brazda, Martin Paclik, Milan Kvicera, Naiallen Carvalho, Tomas Nouza, Ondrej Kozak, Christian Sturm, Automotive Radar - Road Boundary Estimation, International Symposium ELMAR IEEE 202.

Chengming Ye, Jonathan Li, Han Jiang, He Zhao, Lingfei Ma, Michael Chapman, Semi Automated Generation of Road Transition Lines Using Mobile Laser Scanning Data, IEEE Transactions on Intelligent Transportation Systems Vol. 21 (N° 5), IEEE 2020.

Yue Wang, Eam Khwang Teoh and Dinggang Shen, Lane Detection Using B-Snak, Proceedings 1999 International Conference on Information Intelligence and Systems, IEEE 06 August 2002.

Claudio Rosito Jung and Christian Roberto Kelber, A Robust Linear Parabolic Model for Lane Following, Proceedings. 17th Brazilian Symposium on Computer Graphics and Image Processing, 08 November 2004.

Noël Trujillo, Frédéric Chausse, and Roland Chapuis, Objects recognition by focused vision, LASMEA-UMR 6602 UBP/CNRS, 2005.

Sin-Yu Chen and Jun- Wei Hsieh, Edge-based Lane Change Detection and its Application to Suspicious Driving Behavior Analysis, Third International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP 2007).

A. Al Mamun, P. P. Em, J. Hossen, Lane marking detection using simple encode decode deep learning technique: SegNet, International Journal of Electrical and Computer Engineering (IJECE) Vol. 11, (No. 4), August 2021, pp. 3032~3039 ISSN: 2088-8708.

Jun Li, Xue et al, Deep Neural Network for Structural Prediction and Lane Detection in Traffic Scene, IEEE Trans. Neural Networks Learn. Syst., vol. 28, (No. 3), pp. 690-703, 2017.

M. Amine and K. Djoudi, Vehicles detection using the MLP and the correlation measurement, International Conference on Advanced Electrical Engineering (ICAEE), 2019, pp. 1-5, IEEE.

Mazouzi Amine, Kerfa Djoudi, Ismail Rakip Karas, A new method for vehicles detection and tracking using information and image processing, International Journal of Electrical and Computer Engineering (IJECE) Vol. 11, (No. 6), December 2021, pp. 4942~4949 ISSN: 2088-8708.

Mazouzi, A., Bel Bachir, M., Enhancement of the Detection for Intelligent Vehicle Systems - Case Rain/Snow, (2017) International Review of Automatic Control (IREACO), 10 (2), pp. 112-117.

Huifeng Wang, Yunfei Wang, Xiangmo Zhao, Guiping Wang, He Huang, Jiajia Zhang, Lane Detection of Curving Road For Structural Highway With Straight Curve Model On Vision, IEEE Transactions on Vehicular Technology, |Vol 68, (N°6) IEEE, 2019.

Xuan Nie, Yuquan Gao, Fan Gao, Qin Li, Zahid Alam, A Novel Vision Based Road Detection Algorithm for intelligent Vehicle, International Conference on power intelligent computing and systems(ICPICS), IEEE, 2019.

L. A. Feldkamp, D. V. Prokhorov, and T. M. Feldkamp, Simple and conditioned adaptive behavior from Kalman filter trained recurrent networks, Neural Netw., vol. 16, pp. 683-689, Jun./Jul. 2003.

Priya Shree Madhukar, L.B. Prasad, State estimation Using Extended Kalman Filter AND Unscented Kalman Filter, International Conference on Emerging Trends in Communication, Control and Computing (ICONC3), IEEE 2020.

Z. Chen and Z. Chen, RBNet: A deep neural network for unified road and road boundary detection, Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 10634 LNCS, pp. 677-687, 2017.

Shuo Gu, Yigong Zhang, Xia Yuan, Jian Yang, Tao Wu, Hui Kong, Histograms of the Normalized Inverse Depth and Line Scanning for Urban Road Detection, IEEE transaction on Intelligent Transportation Systems, Vol 20 (N°8), IEEE.2019.

Bou Nassif, A., Soudan, B., Azzeh, M., Attilli, I., Almulla, O., Artificial Intelligence and Statistical Techniques in Short-Term Load Forecasting: a Review, (2021) International Review on Modelling and Simulations (IREMOS), 14 (6), pp. 408-430.

José C. Principe, Neil R. Euliano, and W. Curt Lefebuvre, Neuronal and Adaptative Systems (John Wiley and Sons, INC, p. 71-85, 2000).

Salimeh Yasaei Sekeh, Brandon Oselio, Alfred O. Hero, Multi class Bayes errors estimation with a global minimal spanning tree Annual ALLERTON Conference on Communication, Control and Computing, (2018).

J Hang and C Lee, Color Lane Line Detection Using the Bhattacharyya Distance, International Conference on Information, Intelligence, Systems and Applications (IISA), 2020.

X. Yu and Y. Sun, Research on parking detecting analysis based on projection transformation and Hough transform, in Journal of Physics: Conference Series, 2019, vol. 1187, (no. 4).

Sébastien Lefevre, Events detection in the video, Doctoral thesis, University of TOURS, France, 2002.

Habib, T., Replacement of In-Orbit Modern Spacecraft Attitude Determination and Estimation Algorithms with Neural Networks, (2021) International Review of Aerospace Engineering (IREASE), 14 (3), pp. 166-172.

Mohamed Boumediene, Abdelaziz Ouamri, Detection and tracking of the road by vision, Magister thesis, laboratory of signal and image, university USTO Oran, Algeria, 2006.

Eduardo Rodriguez Montero, Markus Vogelsberger,Wolfarm Teppan, Thomas Wolbank, Sensorless Saliency Extraction using Quadratic Regression based Current Derivative Estimation, International Electric Machines and Drives Conference (IEMDC) IEEE, 2021.

L. O. Seman, G. Gomes, R. Hausmann and E. A. Bezerra, A quadratic fuzzy regression approach for handling uncertainties in Partial Least Squares Path Modeling, in IEEE Latin America Transactions, vol. 16, no. 1, pp. 192-201, Jan. 2018.

Dan Levi, Noa Garnett and Ethan Fetaya. StixelNet: A Deep Convolutional Network for Obstacle Detection and Road Segmentation. In Xianghua Xie, Mark W. Jones, and Gary K. L. Tam, editors, Proceedings of the British Machine Vision Conference (BMVC), pages 109.1-109.12. BMVA Press, September 2015.


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