The new arrivals and trends in the technology have attracted many different areas to make the world modernized and smart. The autonomous driverless car is unique example in the category. The aim of this work is to presents a computer vision-based system for real-time traffic sign identification, recognition and retrieval system for Indian traffic signage’s. The system consists of two phases. Firstly the signage’s are detected and recognized for a given video using state-of-art detector method known as aggregated channel features. Second, retrieval of videos is performed using two distance measures known as Euclidean and Jaccard matrices. Compared to the previous approaches our method offers the detection recognition and retrieval of signage’s of different shape and colors in heterogeneous climatic conditions. The results demonstrate the proposed method performs good detection, recognition, and retrieval accuracy with 60 frames per second in less time complexity.

Traffic Signage’s, identification, recognition, retrieval, Traffic Sign recognition system

[1] Andreas Mogelmose, Dongran Liu, Mohan Manubhai Trivedi, “Detection of US Traffic signs”, IEEE Transactions on intelligent transport system, 2015.
[2] Ayoub Elrahyani, Mohamed EL ANSARI, Ilyas EL JAAFARI, “Traffic Sign Detection and Recognition using Features of Combination and Random Forests”, International journal of Advanced Computer Science and Applications, Vol 7, No.1, 2016.
[3] Yuan Yuan, Zhitong Xiong, and Qi Wang, “An Incremental Framework for Video-Based Traffic Sign Detection, Tracking, and Recognition”, IEEE Transactions on Intelligent Transportation Systems, Vol. 18, No. 7, July 2017.
[4] P. Dollar. R.Appel, S.Belongie, and P.Perona, “Fast Feature Pyramids for Object Detection”, Pattern Analysis and Matching Intelligence, IEEE Transactions on, vol.36, no. 8,pp. 1532-1545, Aug 2014.
[5] S. Sathiya, m. Balasubramanian, and, S. Palanivel, “International Journal of Engineering and Technology”, vol.6, no.2, Apr-May 2014.
[6] Aryuanto Soetedjo and I Komang Somawirata, “An Efficient Algorithm for Implementing Traffic Sign Detection on low cost Embedded System”, International Journal of Innovative Computing, Information and Control, vol. 14, no.1, February 2018.
[7] Huda Noor Dean, and Jabir K V.T, “Real Time Detection and Recognition of Indian Traffic Signs using Matlab”, International Journal of Scientific and Engineering research, vol.4, Issue 5, May 2013.
[8] K. Arun Kumar, S.Gowtham, M. Manoj Kumar, and A. Lakshmi, “Automatic Recognition of Sign-Boards using myROI”, International Journal of Pure and Applied Mathematics, vol.119, no.12, 2018.
[9] Markus Mathias, Radu Timofte, Rodrigo Benenson, and Luc Van Gool, “Traffic sign Recognition- How far we are from the solution”, International joint Conference on Neural Networks, ISBN:978-1-4673-6129-3, January 2014.
[10] Hee Seok Lee and Kang Kim, “Simultaneous Traffic Sign Detection and Boundary Estimation using Convolution Neural Network ”, IEEE Transactions on Intelligent Transportation Systems, vol.19, no.5, pp. 1652-1663, Feb 2018.
[11] Shivanand S Gornale, Ashvini K Babaleshwar, Pravin L Yannawar, " Detection and Classification of Signage’s from Random Mobile Videos Using Local Binary Patterns", International Journal of Image, Graphics and Signal Processing(IJIGSP), vol.10, No.2, pp. 52-59, 2018.
[12] Dipika H Patel, “Content-Based Video Retrieval using Enhanced Feature Extraction”, International Journal of Computer Applications 0975-8887, vol.119, pp.4-8, 2015.
[13] Madhav Gitte, Harshal Bawaskar, Sourabh Sethi, Ajinkya Shinde, “Content BasedVideo Retrieval System”, IJRET: International Journal of Researchmin Engineering and Tecnology, vol.3, pp.430-435, 2014.
[14] Milan R.Shetake. Sanjay. B. Waikar, “Content Based Image and Video Retrieval”, Proceedings of 33th IRF International Conference, pp.34-37, 2015.
[15] Navdeep Kaur, Mandeep Singh,“Content-Based Video Retrieval with Frequency domain Analysis using 2- D Correlation Algorithm”, International Journal of Advanced Research in Computer Science and Software Engineering ,vol.4, pp.388-393,2014.
[16] J. Fan, A. K. Elmagarmid, X. Zhu, W. G. Aref, and L. Wu, “Classview: hierarchical video shot classification, indexing, and accessing”, Multimedia, IEEE Transactions , pp. 70–86, 2004.
[17] Xingxiao Wu, Dong Xu, LixinDuan, JieboLuo, "Action Recognition Using MultilevelFeatures and Latent Structural SVM", IEEE Transactions on Circuits and Systems for Video Technology, vol.23, pp.1422-1431, 2013.
[18] Hamdy K. Elminir, Mohamed Abu ElSoud, Sahar F. Sabbeh, Aya Gamal “Multi feature content based video retrieval using high level semantic concept “IJCSI International Journal of Computer Science Issues, vol.9, pp.254-260, 2012.
[19] B. V. Patel, A. V. Deorankar, B. B. Meshram, "Content Based Video Retrieval using Entropy, Edge Detection, Black and White Color Features", Proc. 2nd International Conference on Computer Engineering and Technology (ICCET), vol.6, pp.V6-272 - V6-276, 2010
[20] S. B. Mahalakshmi, Capt. Dr.Santhosh Baboo, “Efficient Video Feature Extraction and Retrieval on Multimodal Search”, International Journal of Advanced Research in Computer and Communication Engineering, vol.4, pp.355-357, 2015.
[21] D.Asha, Madhavee Lata, V.S.K. Reddy, “Content based video retrieval system using Multiple Features”, International Journal of pure and Applied Mathematics, vol. 118, pp.287-294, 2018.
[22] Avinash N Bhute and B B Meshram, “System Analysis and Design for Multimedia Retrieval Systems”, The International Journal of Multimedia and Its Applications (IJMA), vol.5, pp.25-44, 2013.
[23] Tam T. Le, Son T. Tran, SeichiiMita, and ThucD.Nguyen, “Real Time Trafffic sign Detection using Color and Shape-Based Features”, ACIIDS 2010, partII, LNAI 5991, pp.268-278, 2010, springer-verlag berlin Heidelbery 2010.
[24] Shanxin Zhang, Cheng Wang, ZhuangY, Chenglu Wen, Jonathan Li, and Chenhui Yang, “Traffic Sign Timely Visual RecognizabilityEvalution Based on 3D measurable point clouds”, Journal of LATEX class Files, vol.14, No.8,August 2015.
[25] Chu-Hong Hoi, Wei Wang, and Michael R. Lyu, 2003, “A Novel Scheme for Video Similarity Detection”, Department of Computer Science and Engineering, the Chinese University of Hong Kong ©Springer-Verlag Berlin Heidelberg. Pp.373–382, 2003.
[26] Yasira Beevi C P et.al.2009, “An efficient Video Segmentation Algorithm with real time Adaptive Threshold Technique ”, International Journal of Signal Processing, Image Processing and Pattern Recognition vol.2, pp.13-27.
[27] Wu, Chuan, Yuwen He, Li Zhao, and Yuzhuo Zhong. "Motion feature extraction scheme for content-based video retrieval." In Electronic Imaging 2002, pp. 296-305. International Society for Optics and Photonics, 2001.
[28] T.N.Shanmugam, and Priya Rajendran “An Enhanced Content-Based Video Retrieval System Based on QueryClip”, International Journal of Research and Reviews in Applied Sciences, vol.1, pp.236-253, 2009.
[29] Hong Jiang Zhang ,Jianhua Wu, Di Zhong and Stephen W. Smoliar “An Integrated System For Content-Based Video Retrieval And Browsing”,Institute of System Science, National university of Singapore Pattern recoganition. vol.30, pp.643-658, 1997.
[30] Jaimon Jacob, Sudeep Ilayidon, V.P.Devassia, “Content Based Video Retrieval System Using Video Indexing”, Internation Journal of Computer Sciences and Engineering, vol.7, Issue.4, pp.478-482, 2019.