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    HD number plate localization and character segmentation on the Zynq heterogeneous SoC.

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    Authors
    Al-Zawqari, Ali cc
    Hommos, Omar
    Al-Qahtani, Abdulhadi
    Farhat, Ali
    Bensaali, Faycal cc
    Zhai, Xiaojun cc
    Amira, Abbes
    Affiliation
    Qatar University
    University of Derby
    Issue Date
    2018-02-06
    
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    Abstract
    Automatic number plate recognition (ANPR) systems have become widely used in safety, security, and commercial aspects. A typical ANPR system consists of three main stages: number plate localization (NPL), character segmentation (CS), and optical character recognition (OCR). In recent years, to provide a better recognition rate, high-definition (HD) cameras have started to be used. However, most known techniques for standard definition (SD) are not suitable for real-time HD image processing due to the computationally intensive cost of processing several-folds more of image pixels, particularly in the NPL stage. In this paper, algorithms suitable for hardware implementation for NPL and CS stages of an HD ANPR system are presented. Software implementation of the algorithms was carried on as a proof of concept, followed by hardware implementation on a heterogeneous system-on-chip (SoC) device that contains an ARM processor and a field-programmable gate array (FPGA). Heterogeneous implementation of these stages has shown that this HD NPL algorithm can localize a number plate in 16.17 ms, with a success rate of 98.0%. The CS algorithm can then segment the detected plate in 0.59 ms, with a success rate of 99.05%. Both stages utilize only 21% of the available on-chip configurable logic blocks.
    Citation
    Al-Zawqari, A. et al (2018) 'HD number plate localization and character segmentation on the Zynq heterogeneous SoC', Journal of Real-Time Image Processing, DOI 10.1007/s11554-017-0747-7
    Publisher
    Springer
    Journal
    Journal of Real-Time Image Processing
    URI
    http://hdl.handle.net/10545/622890
    DOI
    10.1007/s11554-017-0747-7
    Additional Links
    http://link.springer.com/10.1007/s11554-017-0747-7
    Type
    Article
    Language
    en
    ISSN
    18618200
    EISSN
    18618219
    ae974a485f413a2113503eed53cd6c53
    10.1007/s11554-017-0747-7
    Scopus Count
    Collections
    Department of Electronics, Computing & Maths

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