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

Publication: 
Springer Articles
Author(s): 
F. Javier Toledo, J. Javier Martìnez, F. Javier Garrigòs and J. Manuel Ferràndez
Journal or Conference: 
IWANN 2005, LNCS 3512, pp. 906–912, 2005
Publisher: 
J. Cabestany, A. Prieto, and D.F. Sandoval - © Springer-Verlag Berlin Heidelberg 2005
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.

Resource URL: 

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.