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Optical Character Recognition for Alphanumerical Character Verification in Video Frames

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Artificial Intelligence and Evolutionary Algorithms in Engineering Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 324))

Abstract

In real world, optical character recognition (OCR) is one of the key terms challenging image processing stream. Various applications are emerging based on OCR; one fine good example of these terms was recognizing vehicle’s number plate in tolls. Since various researchers are under strong discussion in this area, here we proposed a new algorithm for recognizing the characters from the motion pictures. Our proposed model is subjected to two major segregations: One is for character mapping and another one is for character verification. Experimental results have been enclosed with an accuracy level of 97.08 %.

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References

  1. R. Lienhart, F. Stuber, Automatic text recognition in digital videos, in Proceedings SPIE, Image and Video Processing IV. (1995) pp. 2666–2675

    Google Scholar 

  2. X. Chen, J. Yang, J. Zhang, A. Waibel, Automatic detection and recognition of signs from natural scenes. IEEE Trans. Image Process. 13, 87–99 (2004)

    Article  Google Scholar 

  3. V. Wu, R. Manmatha, E.M. Riseman, Text finder: an automatic system to detect and recognize text in images. IEEE Trans. Pattern Anal. Mach. Intell. (1999)

    Google Scholar 

  4. J. Ohya, A. Shio, A. Akamatsu, Recognition of characters in scene images. IEEE Trans. Pattern Anal. Mach. Intell. 16, 214–220 (1994)

    Article  Google Scholar 

  5. J. Canny, A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 6, 679–698 (1986)

    Article  Google Scholar 

  6. R. Gonzalez, R. Woods, Digital Image Processing (Addison Wesley, Boston, 1992), pp. 414–428

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, NMAM Institute of Technology, Nitte, Karnataka, India

    Sheshank Shetty & Arun S. Devadiga

  2. Department of Computer Science and Engineering, Vel Tech University, Chennai, India

    S. Sibi Chakkaravarthy, K. A. Varun Kumar, Ethala Kamalanaban & P. Visu

Authors
  1. Sheshank Shetty
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  2. Arun S. Devadiga
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  3. S. Sibi Chakkaravarthy
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  4. K. A. Varun Kumar
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  5. Ethala Kamalanaban
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  6. P. Visu
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Corresponding author

Correspondence to Sheshank Shetty .

Editor information

Editors and Affiliations

  1. Electrical & Electronics Engineering, Noorul Islam Centre for Higher Education, Kumaracoil, Tamil Nadu, India

    L. Padma Suresh

  2. Electrical and Electronics Engineering, SRM Engineering College, Kattankulathur, Tamil Nadu, India

    Subhransu Sekhar Dash

  3. Electrical Engineering, IIT Delhi, New Delhi, Delhi, India

    Bijaya Ketan Panigrahi

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Shetty, S., Devadiga, A.S., Chakkaravarthy, S.S., Varun Kumar, K.A., Kamalanaban, E., Visu, P. (2015). Optical Character Recognition for Alphanumerical Character Verification in Video Frames. In: Suresh, L., Dash, S., Panigrahi, B. (eds) Artificial Intelligence and Evolutionary Algorithms in Engineering Systems. Advances in Intelligent Systems and Computing, vol 324. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2126-5_10

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  • DOI: https://doi.org/10.1007/978-81-322-2126-5_10

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2125-8

  • Online ISBN: 978-81-322-2126-5

  • eBook Packages: EngineeringEngineering (R0)

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