A Semantic Extraction and Analysis for Traffic Density Using Traffic Images: A Critical Review

Ruhana Abang Yusup, Wang Hui Hui, Wee Bui Lin

Abstract


Population growth in large cities has contributed to the increase in vehicles' number, leading to the traffic congestion problem. Incompetent traffic supervision could squander an inconsiderable number of man-hours and might lead to fatal consequences. Therefore, intelligent traffic surveillance systems have to carry more significant roles in highway monitoring and traffic management system throughout the years. Although vehicle detection and classification methods have evolved rapidly throughout the years, they still lack high-level reasoning. Accurate and precise vehicle recognition and classification are still insufficient to develop an intelligent and reliable traffic system. There is a demand to increase the confidence in image understanding and effectively extract the images conformed to human perception and without human interference. This paper attempts to summarize a review on several methods that semantically extract and analyze traffic density with image processing techniques. Three (3) methods that have been selected to be discussed in this paper are semantic analysis of traffic video using image understanding, mining semantic context details of traffic scene, and integrating vision and language in semantic description of traffic events from image sequences. Each method is discussed thoroughly, and their outstanding issue is deliberated in this paper.


Keywords


Intelligent traffic surveillance; semantical analysis; traffic images; traffic density.

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References


A. Joshi and D. Mishra, “Review of traffic density analysis techniques,†International Journal of Advanced Research in Computer and Communication Engineering, vol. 4, no. 7, pp. 209-213, July 2015.

B. Narang and P. Kochar, “Real time traffic light controller,†International Journal of Computer Technology and Applications, vol. 5, no. 3, pp. 1092-1096, May 2014.

U. Nagaraj, J. Rathod, P. Patil, S. Thakur, and U. Sharma, “Traffic jam detection using image processing,†International Journal of Engineering Research and Applications (IJERA), vol. 3, no. 2, pp. 1087-1091, March 2013.

V. Dangi, A. Parab, K. Pawar, and S. S. Rathod, “Image processing based intelligent traffic controller,†Undergraduate Academic Research Journal (UARJ), vol. 1, no. 1, pp. 1-17, 2012.

N. Lende and S. S. Paygude, “Survey on traffic monitoring system using image processing,†International Journal of Advanced Reseacrh in Computer Engineering & Technology (IJARCET), vol. 3, no. 12, pp. 4374-4377, Dec. 2014.

H. H. Wang, D. Mohammad, and N. A. Ismail, “An efficient parameters selection for object recognition based colour features in traffic image retrieval,†The International Arab Journal of Information Technology, vol. 11, no. 3, pp. 308-314, May 2014.

J. Wu, Z. Cui, H. Yue, and G. Zhang, “Semantic analysis of traffic video using image understanding,†Journal Of Multimedia, vol. 7, no. 1, pp. 41-48, Feb. 2012.

T. Zhang, S. Liu, C. Xu, and H. Lu, “Mining semantic context information for intelligent video surveillance of traffic scenes,†IEEE Transactions on Industrial Informatics, vol. 9, no. 1, pp. 149-160, Feb. 2013.

T. Hirano, S. Yoneyama, Y. Okada, and Y. Kosugi, “Integrating Vision and Language: Semantic Description of Traffic Events from Image Sequences,†International Symposium on Visual Computing, 2007, pp. 459-468.

O. Tozel, F. Porikli, and P. Meer, “A Bayesian Approach to Background Modeling,†IEEE Workshop on Machine Vision for Intelligent Vehicles (MVIV), vol. 3, pp. 58-65, June 2005.

S. S. Harsha and Ch. Sandeep, “Real time traffic density and vehicle count using image processing technique,†International Journal of Research in Computer and Communication Technology (IJRCCT), vol. 4, no. 8, pp. 594-598, Aug. 2015.

H. Haeikki, S. Y. Fatemeh, and Chen, K., “Car type recognition with deep neural networks,†IEEE Intelligent Vehicles Symposium (IV), pp. 1115-1120, June 2016.

Y. Tang, C. Zhang, R. Gu, and P. Li, “Vehicle detection and recognition for intelligent traffic surveillance system,†Multimedia Tools and Applications, vol. 76, no. 4, pp. 5817-5832, Feb. 2017.

B. Sharma, V. K. Katiyar, A. K. Gupta and A. Singh, “The automated vehicle detection of highway traffic images by differential morphological profile,†Journal Of Transportation Technologies, vol. 4, no. 2, pp. 150-156, Apr. 2014.

K. Garg, S. Lam, T. Srikanthan, and V. Agarwal “Real-time road traffic density estimation using block variance,†2016 IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Placid, NY, 2016, pp. 1-9..

S. Ojha and S. Sakhare, “Image processing techniques for object tracking in video surveillance- A survey,†2015 International Conference on Pervasive Computing (ICPC), Pune, 2015, pp. 1-6.

Z. Dong, Y. Wu, M. Pei, and Y. Jia, “Vehicle type classification using a semisupervised convolutional neural network,†IEEE Transactions on Intelligent Transportation Systems, vol. 16, no. 4, pp. 2247-2256, Aug. 2015.

S. Qu, Y. Xi, and S. Ding, “Image caption description of traffic scene based on deep learning,†Journal of Northwestern Polytechnical University, vol. 36, no. 3, pp. 522-526, June 2018.

N. Abid, T. Ouni and M. Abid, “Vehicle detection for intelligent traffic surveillance system,†2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), Sousse, Tunisia, 2020, pp. 1-5.

N. Audebert, B. L. Saux, and S. Lefevre, “Segment-before-detect vehicle detection and classification through semantic segmentation of aerial images,â€, Remote Sensing, vol. 9, no. 4, pp. 1-18, Apr. 2017.

Y. Tian, Y. Wang, R. Song and H. Song, “Accurate vehicle detection and counting algorithm for traffic data collection,†2015 International Conference on Connected Vehicles and Expo (ICCVE), Shenzhen, 2015, pp. 285-290.

L. Suhao, L. Jinzhao, L. Guoquan, B. Tong, W. Huiqian and P. Yu, “Vehicle type detection based on deep learning in traffic scene,†Procedia Computer Science, vol. 131, pp. 564-572, Jan. 2018.

Y. Zhou and N. Cheung, “Vehicle classification using transferable deep neural network features,†International Journal of Advanced Research in Computer and Communication Engineering, vol. 4, no. 7, pp. 209-213, Jan. 2016.

V. Vijayaraghavan and M. Laavanya, “Vehicle classification and detection using deep learning,†International Journal of Engineering and Advanced Technology (IJEAT), vol. 9, no. 1S5, pp. 24-28, Dec. 2019.

S. Kul, S. Eken and A. Sayar, “A concise review on vehicle detection and classification,†2017 International Conference on Engineering and Technology (ICET), vol. 4, no. 7, pp. 1-4, Aug. 2017.

K. V. Sakhare, T. Tewari and V. Vyas, “Review of vehicle detection systems in advanced driver assistant systems,†Archives of Computational Methods in Engineering, vol. 27, pp. 591-610, March 2019.

W. Li and H. Dai, “Real-time road congestion detection based on image texture analysis,†Procedia Engineering, vol. 137, pp. 196-201, Dec. 2016.

Y. Wang, X. Ban, H. Wang, D. Wu, H. Wang, S. Yang, S. Liu and J. Lai, “Detection and classification of moving vehicle from video using Multiple Spatio-Temporal Features,†IEEE Access, vol. 7, pp. 80287-80299, June 2019.

A. Mukhtar, L. Xia, and T. B. Tang, “Vehicle detection techniques for collision avoidance systems,†IEEE Transactions on Intelligent Transportation Systems, vol. 16, no. 5, pp. 2318-2338, Oct. 2015.

K. Liu and G. Mattyus, “Fast multiclass vehicle detection on aerial images†IEEE Geoscience and Remote Sensing Letters, vol. 12, no. 9, pp. 1938-1942, Sep. 2015.

D. Sahgal, Dr. A. Ramesh, and Pof. M. Parida, “Real-time vehicle queue detection at urban traffic intersection using image processing,†International Journal of Engineering Science and Generic Research (IJESAR), vol. 4, no. 2, pp. 12-15, Apr. 2018.

X. Wen, L. Shao, W. Fang, and Y. Xue, “Efficient feature selection and classification for vehicle detection,†IEEE Transactions on Circuits and Systems for Video Technology, vol. 25, no. 3, pp. 508-517, March 2015.

M. S. Uddin, A. K. Das, and M. A. Taleb, “Real-time area-based traffic density estimation by image processing for traffic signal control system: Bangladesh perspective,†2015 International Conference on Electrical Engineering and Information Communication Technology (ICEEICT), Dhaka, pp. 1-5, 2015.

R. Takeuchi, K. Kato, D. Harwood, and L. S. Davis, “Vehicle detection using PLS Hough transform,†2015 21st Korea-Japan Joint Workshop on Frontiers of Computer Vision, Mokpo, 2015, pp. 1-6.

A. Bartsch, F. Fitzek, and R. Rasshofer, “Padesterian recognition using automotive radar sensorsâ€, Advances in Radio Sciences. vol. 10, pp. 45-55, Sep. 2012.

V. Keerthi Kiran, P., Parida, and S. Dash, “Vehicle detection and classification: a review,†10th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA), Odisha, India, 2019, pp. 45-56.

A. Arinaldi, J. A. Pradana, and A. A, Gurusinga “Detection and classification of vehicles for traffic video analytics,†Procedia Computer Science, vol. 144, pp. 259-268, 2018.

C. Tsai, C. Tseng, H. Tang, and J. Guo, “Vehicle detection and classification based on Deep Neural Network for intelligent transportation applications,†2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Honululu, HI, USA, 2018, pp. 1605-1608.




DOI: http://dx.doi.org/10.18517/ijaseit.10.1.10195

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