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Image Processing with CNN in a FPGA-Based Augmented Reality System for Visually Impaired People

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Part of the book series:Lecture Notes in Computer Science ((LNTCS,volume 3512))

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Abstract

A cellular neural network is proposed as the main processing core in a novel FPGA-based augmented reality system. The described application is focused on visually impaired people aid. The aim is to enhance the user’s knowledge of the environment with useful information extracted by image processing. A CNN architecture oriented to hardware implementation on FPGA is presented, and used as the image processor in a fully FPGA-based system. So, CNNs and FPGAs are combined in a system which makes the most of their characteristics to achieve high performance and versatility.

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Author information

Authors and Affiliations

  1. Dpto. Electrónica, Tecnología de Computadoras y Proyectos, Universidad Politécnica de Cartagena, 30202, Cartagena, Spain

    F. Javier Toledo, J. Javier Martínez, F. Javier Garrigós & J. Manuel Ferrández

Authors
  1. F. Javier Toledo

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  2. J. Javier Martínez

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  3. F. Javier Garrigós

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  4. J. Manuel Ferrández

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Editor information

Editors and Affiliations

  1. Departamento de Ingeniería Electrónica, Universitat Politècnica de Catalunya (UPC). E.T.S.I. de Telecomunicación, Campus Norte, Edificio C4, C/ Jordi Girona, 1-3, E08034, Barcelona, Spain

    Joan Cabestany

  2. Department of Computer Architecture and Computer Technology, University of Granada,  

    Alberto Prieto

  3. Grupo ISIS, Dpto. Tecnología Electrónica ETSI Telecomunicación, Universidad de Málaga, Campus de Teatinos, 29071, Málaga, Spain

    Francisco Sandoval

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© 2005 Springer-Verlag Berlin Heidelberg

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Toledo, F.J., Martínez, J.J., Garrigós, F.J., Ferrández, J.M. (2005). Image Processing with CNN in a FPGA-Based Augmented Reality System for Visually Impaired People. In: Cabestany, J., Prieto, A., Sandoval, F. (eds) Computational Intelligence and Bioinspired Systems. IWANN 2005. Lecture Notes in Computer Science, vol 3512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11494669_111

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