Intelligent Transportation System by Controlling Traffic using Video Processing in Mat Lab
Vijay.J1, Akshaykumar.K2, Jeevarathinam.K3, Sriram.D4, Anand.K5

1Vijay.J, Assistant Professor (G-II)/ ECE, Aarupadaiveedu Institute of Technology, Kanchipuram, (Tamil Nadu), India.
2Akshaykumar.K, Students, Third Year- ECE, JeppiaarMaamallan Engineering College, Kanchipuram, (Tamil Nadu), India.
3Jeevarathinam.K, Students, Third Year- ECE, Jeppiaar Maamallan Engineering College, Kanchipuram, (Tamil Nadu), India.
4Sriram.D, Students, Third Year- ECE, JeppiaarMaamallan Engineering College, Kanchipuram, (Tamil Nadu), India.
5Anand.K, 5Student, Third Year- EEE, JeppiaarMaamallan Engineering College, Kanchipuram, (Tamil Nadu), India.

Manuscript received on 03 August 2019. | Revised Manuscript received on 09 August 2019. | Manuscript published on 30 September 2019. | PP: 8046-8049 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6426098319/2019©BEIESP | DOI: 10.35940/ijrte.C6426.098319

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Abstract: Laptop vision techniques square measure used for analysis of traffic police investigation videos that is gaining a lot of importance. This analysis of videos is helpful for public safety and for traffic management. In recent time, there has been Associate in nursing exaggerated scope for analysis of traffic activity mechanically. Laptop based mostly police investigation algorithms and systems square measure won’t to extract info from the videos that is additionally known as as Video analytics. The method of distinguishing instances of planet objects is understood as object detection. It detects the quantity of vehicles on every road and betting on the vehicles load on every road, this technique assigns optimized quantity of waiting time (red signal light) and period (green signal light). This technique could be a totally machine-driven system that may replace the traditional pre-determined fixed-time based mostly traffic system with a dynamically managed traffic system.
Keywords: Object Detection, Video Analysis, Bounding Box, Holes Filling, KNN Classifier.

Scope of the Article:
Evolutionary Computing and Intelligent Systems