• DocumentCode
    2776350
  • Title

    Car plate recognition based on UMACE filter

  • Author

    Noor, Siti Salwa Md ; Tahir, Nooritawati Md

  • Author_Institution
    Fac. of Electr. Eng., Univ. Teknol. MARA, Shah Alam, Malaysia
  • fYear
    2010
  • fDate
    5-8 Dec. 2010
  • Firstpage
    655
  • Lastpage
    658
  • Abstract
    In this work, the Automatic Parking and Retrieval System (APRS) is proposed to overcome the parking space problem. This system will save space, time, environment and security. The main part that involves in this system is car plate identification and recognition. The plate recognition is used as an identity number to park the car into the available parking space or slot. Therefore in this paper, car plate recognition based on Unconstrained Minimum Average Correlation Energy (UMACE) filter is discussed. Peak to Side lobe Ratio (PSR) is used as a performance measure via the sharpness of the correlation peak. The implementation involved only two stages, as compared to conventional method that consisted of segmentation stage of character. Over hundred images are used as database to evaluate the method and results showed that the proposed method is able to classify car plate with good accuracy.
  • Keywords
    filtering theory; image recognition; image segmentation; traffic engineering computing; UMACE filter; automatic parking and retrieval system; car plate identification; car plate recognition; character segmentation stage; correlation peak sharpness measurement; peak-to-side lobe ratio; unconstrained minimum average correlation energy; Character recognition; Correlation; Databases; Image recognition; Licenses; Lighting; Training; APSR; PSR; UMACE; detection; recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Applications and Industrial Electronics (ICCAIE), 2010 International Conference on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4244-9054-7
  • Type

    conf

  • DOI
    10.1109/ICCAIE.2010.5735016
  • Filename
    5735016