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Real-Time Local Train Tracking System through HaarCascade Classifier and OCR Model

S. Sarkar1 , S. Lahiri2 , A. Biswas3 , A. Das4 , S. Bhowmick5 , S. Sahana6 , D. Singh7 , I. Nath8

Section:Research Paper, Product Type: Journal Paper
Volume-08 , Issue-01 , Page no. 32-36, Feb-2020

Online published on Feb 28, 2020

Copyright © S. Sarkar, S. Lahiri, A. Biswas, A. Das, S. Bhowmick, S. Sahana, D. Singh, I. Nath . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: S. Sarkar, S. Lahiri, A. Biswas, A. Das, S. Bhowmick, S. Sahana, D. Singh, I. Nath, “Real-Time Local Train Tracking System through HaarCascade Classifier and OCR Model,” International Journal of Computer Sciences and Engineering, Vol.08, Issue.01, pp.32-36, 2020.

MLA Style Citation: S. Sarkar, S. Lahiri, A. Biswas, A. Das, S. Bhowmick, S. Sahana, D. Singh, I. Nath "Real-Time Local Train Tracking System through HaarCascade Classifier and OCR Model." International Journal of Computer Sciences and Engineering 08.01 (2020): 32-36.

APA Style Citation: S. Sarkar, S. Lahiri, A. Biswas, A. Das, S. Bhowmick, S. Sahana, D. Singh, I. Nath, (2020). Real-Time Local Train Tracking System through HaarCascade Classifier and OCR Model. International Journal of Computer Sciences and Engineering, 08(01), 32-36.

BibTex Style Citation:
@article{Sarkar_2020,
author = {S. Sarkar, S. Lahiri, A. Biswas, A. Das, S. Bhowmick, S. Sahana, D. Singh, I. Nath},
title = {Real-Time Local Train Tracking System through HaarCascade Classifier and OCR Model},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {2 2020},
volume = {08},
Issue = {01},
month = {2},
year = {2020},
issn = {2347-2693},
pages = {32-36},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1395},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1395
TI - Real-Time Local Train Tracking System through HaarCascade Classifier and OCR Model
T2 - International Journal of Computer Sciences and Engineering
AU - S. Sarkar, S. Lahiri, A. Biswas, A. Das, S. Bhowmick, S. Sahana, D. Singh, I. Nath
PY - 2020
DA - 2020/02/28
PB - IJCSE, Indore, INDIA
SP - 32-36
IS - 01
VL - 08
SN - 2347-2693
ER -

           

Abstract

Indian railways are one of the most vast and complex railway networks in the world in which majority of the population is dependent. But such vast and complex system comes with a cost, the real time tracking which are implemented by railways using GPS tracking mechanism is far from accuracy. People get annoyed due to late arrival of passenger trains and wish to switch to other means of transport. There is a lot of wastage of time and money of the passengers due to this unscheduled timing of trains where passengers are unaware of time at which the train actually leaves the station. Although efforts like “Where Is My Train” by Sigmoid Labs have managed overcoming this situation to an extent but it’s operating principle is not enough for keeping exact track of such a huge network and we users are quite aware about its limitation and discrepancies regarding real time train’s location. In this manuscript, we are proposing a real time local train tracking using surveillance camera. OCR based Computer Vision model is developed in order to fetch status of trains from the snaps and accordingly relevant data is generated and updated in the main frame server. CCTV’s installed at stations ends are utilized for this purpose the feed from these cams are passed to our OCR Model & the data collected or analysed from those feed is further uploaded & updated in the database. Data refers to train name, number & time stamp. Users are provided with an app through which they can keep an exact track of passenger train’s arrival & departure on a real time basis.

Key-Words / Index Term

Local Train tracking, Computer Vision, Haar-Cascade, Optical Character Recognition (OCR), Tesseract v4

References

[1] Al Rashed, M. A., Oumar, O. A., & Singh, D. (2013). A real time GSM/GPS based tracking system based on GSM mobile phone.
[2] Second International Conference on Future Generation Communication Technologies (FGCT 2013). doi:10.1109/fgct.2013.6767186
[3] Prajapati, S., Joshi, S. R., Maharjan, A., & Balami, B. (2018).
[4] Evaluating Performance of Nepali Script OCR using Tesseract and Artificial Neural Network.
[5] 2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS). doi:10.1109/cccs.2018.8586808
[6] Kumar, G. H., & Ramesh, G. P. (2017). Intelligent gateway for real time train tracking and railway crossing including emergency path using D2D communication. 2017 International Conference on Information Communication and Embedded Systems (ICICES). doi:10.1109/icices.2017.8070779
[7] Optical Character Recognition by Open Source OCR
[8] Tool Tesseract: A Case Study International Journal of Computer Applications (0975 – 8887) Volume 55– No.10, October 2012
[9] Nurhayati, Risda, B. C., & Masruroh, S. U. (2014). (Optical Character Recognition using Tesseract)
[10] Optical character recognition feature implementation in cooking recipe application using tesseract Google project.
[11] 2014 International Conference on Cyber and IT Service Management (CITSM). doi:10.1109/citsm.2014.7042173
[12] Alexander, A., & Dharmana, M. M. (2017). Object detection algorithm for segregating similar coloured objects and database formation. 2017 International Conference on Circuit, Power and Computing Technologies (ICCPCT). doi:10.1109/iccpct.2017.8074332
[13] Ashwini, B., Yuvaraju, B. N., Pai, A. Y., & Aditya Baliga, B. (2017).
[14] Real Time Detection and Classification of Vehicles and Pedestrians Using Haar Cascade Classifier with Background Subtraction.
[15] 2017 2nd International Conference on Computational Systems and Information Technology for Sustainable Solution (CSITSS). doi:10.1109/csitss.2017.8447818
[16] Li, Q., An, W., Zhou, A., & Ma, L. (2016). (Optical Character Recognition using Tesseract)
[17] Recognition of Offline Handwritten Chinese Characters Using the Tesseract Open Source OCR Engine.
[18] 2016 8th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC). doi:10.1109/ihmsc.2016.239
[19] Abdallah Dafallah, H. A. (2014).
[20] Design and implementation of an accurate real time GPS tracking system.
[21] The Third International Conference on e-Technologies and Networks for Development (ICeND2014). doi:10.1109/icend.2014.6991376
[22] Nelson, L. M., & Levine, J. (n.d.).
[23] Understanding limitations of open carrier phase frequency transfer on a transatlantic baseline.
[24] Proceedings of the 2001 IEEE International Frequncy Control Symposium and PDA Exhibition (Cat. No.01CH37218). doi:10.1109/freq.2001.956187
[25] Nikolic, M. V., Kosic, B. D., Milanovic, M. D., Antonic, N. M., Stojkovic, Z. M., & Kokic, I. Z. (2014). Railway axle counter prototype. 2014 22nd Telecommunications Forum Telfor (TELFOR). doi:10.1109/telfor.2014.7034503