Real-Time Local Train Tracking System through HaarCascade Classifier and OCR Model
Keywords:
Local Train tracking,, Computer Vision, Haar-Cascade, Tesseract v4, Optical Character Recognition (OCR)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.
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