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Artificial Neural Network for Character Recognition on Embedded-Based FPGA

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Future Information Technology

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 309))

Abstract

An embedded system application involves a diverse set of skills that extend across traditional disciplinary boundaries, including computer hardware, software, algorithms, interfacing and application domain. Field Programmable Gate Arrays (FPGAs) which offer flexibility in design like software, but with performance speeds closer to Application Specific Integrated Circuits (ASICs) are used as an embedded-based system in this project. The character recognition project using artificial neural network (ANN) approach is implemented on Altera Cyclone II 2C35 FPGA device and the results shown very promising.

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Author information

Authors and Affiliations

  1. School of Computer and Communication Engineering, Universiti Malaysia Perlis, Pauh Putra Campus, 02060, Arau, Perlis, Malaysia

    Phaklen Ehkan, Lee Yee Ann, Fazrul Faiz Zakaria & M. Nazri M. Warip

Authors
  1. Phaklen Ehkan
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  2. Lee Yee Ann
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  3. Fazrul Faiz Zakaria
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  4. M. Nazri M. Warip
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Corresponding author

Correspondence to Phaklen Ehkan .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Seoul National University of Science & and Technology (SeoulTech), Seoul, Korea, Republic of (South Korea)

    James J. (Jong Hyuk) Park

  2. Department of Computer Science, Georgia State University, Atlanta, Georgia, USA

    Yi Pan

  3. Digital Media Engineering, Anyang University, Anyang, Korea, Republic of (South Korea)

    Cheon-Shik Kim

  4. Information & Communication Technologies, Swinburne University of Technology, Melbourne, Victoria, Australia

    Yun Yang

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© 2014 Springer-Verlag Berlin Heidelberg

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Ehkan, P., Ann, L.Y., Zakaria, F.F., Warip, M.N.M. (2014). Artificial Neural Network for Character Recognition on Embedded-Based FPGA. In: Park, J., Pan, Y., Kim, CS., Yang, Y. (eds) Future Information Technology. Lecture Notes in Electrical Engineering, vol 309. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55038-6_43

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  • DOI: https://doi.org/10.1007/978-3-642-55038-6_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-55037-9

  • Online ISBN: 978-3-642-55038-6

  • eBook Packages: EngineeringEngineering (R0)

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