Automated Toll Booth using Morphological Edge Detection Algorithm
Kausalya. K1, Bhavadarini. S2, Gayathri. A3
1Mrs. K.Kausalya, Assistant Professor, Department of Information technology, Easwari Engineering college, Chennai, Tamilnadu, India.
2Ms. Bhavadarini S, Studying, Easwari Engineering college, Chennai, Tamilnadu, India.
3Ms. Gayathri, Studying, Easwari Engineering college, Chennai, Tamilnadu, India.

Manuscript received on November 12, 2019. | Revised Manuscript received on November 25, 2019. | Manuscript published on 30 November, 2019. | PP: 5331-5335 | Volume-8 Issue-4, November 2019. | Retrieval Number: D7554118419/2019©BEIESP | DOI: 10.35940/ijrte.D7554.118419

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Abstract: In order to reduce the traffic jam, save time and to diminish the money loss of 300 crores/year, an automated system is proposed; The intelligent traffic control management systems which explains the installation of automation in toll plazas, which is a step towards improving the monitoring of vehicles. The main purpose of this arrangement is to implement a system, which automatically identifies an approaching vehicle and records the vehicles number and time. If the vehicle belongs to an authorized person, the toll gate opens automatically and a predetermined amount is deducted from the user account, which leads to reduce the Traffic clogging at toll plazas. The vehicle number plate recognition is done only for authorized members. The proposed model consists of image digitization, edge detection, character detection and recognition with the payment transaction. The proposed method uses morphological edge detection , for the system to identify the character recognition and it uses template matching; it is done for license plates of 6 characters. The license plate character recognition system can be used in vehicle check -in and checkout monitoring system in hotels, malls and can be used to track vehicles on normal roads other than toll booths to avoid thefts.
Keywords: Traffic Jam, Intelligent Traffic Control Management, Systems, Vehicles, Traffic Clogging.
Scope of the Article: Control and Automation.