Time and Date OCR in CCTV Video

  • Ginés García-Mateos
  • Andrés García-Meroño
  • Cristina Vicente-Chicote
  • Alberto Ruiz
  • Pedro E. López-de-Teruel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)


Automatic recognition of time and date stamps in CCTV video enables the inclusion of time-based queries in video indexing applications. Such ability needs to deal with problems of low character resolution, non-uniform background, multiplexed video format, and random access to the video file. In this paper, we address these problems and propose a technique that solves the difficult task of character segmentation, by means of a recognition-based process. Our method consists of three main steps: pattern matching, character location and syntactic analysis. The experiments prove the reliability and efficiency of the proposed method, obtaining an overall recognition rate over 80%.


Recognition Rate Pattern Match Character Location Decimal Digit Syntactic Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Lienhart, R.: Video OCR: A Survey and Practitioner’s Guide. Video Mining, pp. 155–184. Kluwer Academic Publisher, Dordrecht (2003)Google Scholar
  2. 2.
    Sato, T., Kanade, T., Hughes, E.K., Smith, M.A., Satoh, S.: Video OCR: Indexing Digital News Libraries by Recognition of Superimposed Captions. ACM Multimedia Systems 7(5), 385–395 (1999)CrossRefGoogle Scholar
  3. 3.
    Jain, A.K., Yu, B.: Automatic Text Localication in Images and Video Frames. Pattern Recognition 31(12), 2055–2076 (1998)CrossRefGoogle Scholar
  4. 4.
    Li, H., Doermann, D., Kia, O.: Automatic Text Detection and Tracking in Digital Video. IEEE Trans. on Image Processing 9(1), 147–156 (2000)CrossRefGoogle Scholar
  5. 5.
    Lienhart, R., Pfeiffer, S., Effelsberg, W.: Video Abstracting. Communications of the ACM 40(12), 55–62 (1997)CrossRefGoogle Scholar
  6. 6.
    Yang, J., Chen, X., Zhang, J., Zhang, Y., Waibel, A.: Automatic Detection and Translation of Text from Natural Escenes. In: Proc. of ICASSP 2002, vol. 2 (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Ginés García-Mateos
    • 1
  • Andrés García-Meroño
    • 1
  • Cristina Vicente-Chicote
    • 3
  • Alberto Ruiz
    • 1
  • Pedro E. López-de-Teruel
    • 2
  1. 1.Dept. de Informática y Sistemas 
  2. 2.Dept. de Ingeniería y Tecnología de ComputadoresUniversidad de MurciaEspinardo, MurciaSpain
  3. 3.Dept. Tecnologías de la Información y ComunicacionesUniversidad Politécnica de CartagenaCartagena, MurciaSpain

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