Automatic Tollbooth Credit System using Vehicle detection and Number Identification
Tamilarasu Viswanathan1, M Mathan Kumar2
1Tamilarasu Viswanathan, Assistant Professor, Department of Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore (TamilNadu), India.
2M Mathan Kumar, Assistant Professor, Department of Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore (TamilNadu), India.
Manuscript received on 05 December 2018 | Revised Manuscript received on 12 December 2018 | Manuscript Published on 26 December 2018 | PP: 313-316 | Volume-8 Issue- 2S2 December 2018 | Retrieval Number: BS2069128218/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A computer vision based toll booth credit system is proposed using vehicle (object tracking) detection and Number (text recognition) identification. Set of vehicles database loadedin a predetermine network and support vector machine (SVM) classifier identify the vehicle. Name plate details recognize using optical character recognition (OCR) and corresponding details produce inside the toking scheme with minimal ”imbinarize” global method. Additionally Histogram of Oriented Gradient (HOG) for partitioning the data with extracted feature. The proposed scheme shows the excellent automatic credit system than any-other existing scheme.
Keywords: Object Tracking, Tollbooth, OCR, SVM and HO.
Scope of the Article: Computer Architecture and VLSI