Document Type : Original Article

Author

Department of Computer Science and Technology, Henan Institute of Technology, Xinxiang 453003, China

Abstract

One of the important and more challenging categories in the smart cities and IoT is to monitor the vehicles plate licenses. This system is a key factor in most of the traffic monitoring in the IoT based smart city applications. In this research, a method for plate license recognition based on optimal training of the CNN is proposed. To do this, the configuration and the hyperparameters of the CNN were optimized by a new hybrid optimization including world cup optimizer, whale optimizer, and chaotic theory to obtain a better result with high convergence. Simulations are applied to the UFPR-ALPR dataset and are compared with six popular techniques in terms of accuracy and time. Experimental achievements indicated that the proposed method gives superiority toward the other comparative techniques and is an efficient method for vehicles plate licenses detection.

Keywords

How to cite this article
Sun D. IoT-based Automated Vehicle Plate Detection Algorithm for Urban Surveillance Systems by A New Hybrid Optimized CNN J. Journal of Smart Energy and Sustainability, 2022; 1(2): 105-115. 

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