Deep Classifiers-Based License Plate Detection, Localization and Recognition on GPU-Powered Mobile Platform

Syed Tahir Hussain Rizvi, Denis Patti, Tomas Björklund, Gianpiero Cabodi and Gianluca Francini
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Syed Tahir Hussain Rizvi: Dipartimento di Automatica e Informatica (DAUIN), Politecnico di Torino, 10129 Turin, Italy
Denis Patti: Dipartimento di Automatica e Informatica (DAUIN), Politecnico di Torino, 10129 Turin, Italy
Tomas Björklund: Dipartimento di Elettronica (DET), Politecnico di Torino, 10129 Turin, Italy
Gianpiero Cabodi: Dipartimento di Automatica e Informatica (DAUIN), Politecnico di Torino, 10129 Turin, Italy
Gianluca Francini: Joint Open Lab, Telecom Italia Mobile (TIM), 10129 Turin, Italy

Future Internet, 2017, vol. 9, issue 4, 1-11

Abstract: The realization of a deep neural architecture on a mobile platform is challenging, but can open up a number of possibilities for visual analysis applications. A neural network can be realized on a mobile platform by exploiting the computational power of the embedded GPU and simplifying the flow of a neural architecture trained on the desktop workstation or a GPU server. This paper presents an embedded platform-based Italian license plate detection and recognition system using deep neural classifiers. In this work, trained parameters of a highly precise automatic license plate recognition (ALPR) system are imported and used to replicate the same neural classifiers on a Nvidia Shield K1 tablet. A CUDA-based framework is used to realize these neural networks. The flow of the trained architecture is simplified to perform the license plate recognition in real-time. Results show that the tasks of plate and character detection and localization can be performed in real-time on a mobile platform by simplifying the flow of the trained architecture. However, the accuracy of the simplified architecture would be decreased accordingly.

Keywords: convolutional neural network; visual analysis; embedded platforms; general purpose GPU; license plate detection (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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