Hardware Synthesize and Performance Analysis of Intelligent Transportation Using Canny Edge Detection Algorithm

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Author(s)

Aisha Baloch 1,* Tayab D Memon 2,3 Farida Memon 2 Bharat Lal 2 Ved Viyas 1 Tony Jan 3

1. Institute of Information Communication and Technologies, Mehran University of Engineering and Technology, Jamshoro, Pakistan

2. Department of Electronic Engineering, Mehran University of Engineering and Technology, Jamshoro, Pakistan.

3. School of Information Technology and Engineering, Melbourne Institute of Technology, Melbourne, Australia

* Corresponding author.

DOI: https://doi.org/10.5815/ijem.2021.04.03

Received: 10 Apr. 2021 / Revised: 20 May 2021 / Accepted: 16 Jun. 2021 / Published: 8 Aug. 2021

Index Terms

Intelligent Transportation, vehicle detection and classification, Xilinx system generator, Zedboard FPGA board, Xilinx Platform, DVI connector.

Abstract

The World is moving toward Smart traffic management and monitoring technologies. Vehicle detection and classification are the two important features of intelligent transportation system. Several algorithms for detection of vehicles such as Sobel, Prewitt, and Robert etc. but due to their less accuracy and sensitivity to noise they could not detect vehicles clearly. In this paper, a simple and rapid prototyping approach for vehicle detection and classification using MATLAB Xilinx system generator and Zedboard is presented. The Simulink model of vehicle detection and classification is designed using a complex canny edge detection algorithm for vehicle detection. The canny edge detection algorithm offers 91% accuracy as compared to its counterpart Sobel and Perwitt algorithms that offer 79.4% and 76.1% accuracy. The feature vector approach is used for vehicle classification. The proposed model is simulated and validated in MATLAB. The Canny edge detection and feature vector algorithms for vehicle detection and classification are synthesized through the Xilinx system generator in Zedboard. The proposed design is validated with the existing works. The implementation results reveal that the proposed system for vehicle detection and classification takes only 8 ns of execution time with a 128MHz clock, which is the lowest and optimum calculation period for the smart city.

Cite This Paper

Aisha Baloch, Tayab D Memon, Farida Memon, Bharat Lal, Ved Viyas, Tony Jan, " Hardware Synthesize and Performance Analysis of Intelligent Transportation Using Canny Edge Detection Algorithm", International Journal of Engineering and Manufacturing (IJEM), Vol.11, No.4, pp. 22-32, 2021. DOI: 10.5815/ijem.2021.04.03

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