Image processing with CNN in a FPGA-Based augmented reality system for visually impaired people

Authors:
F. Javier Toledo;J. Javier Martínez;F. Javier Garrigós;J. Manuel Ferrández
Affiliations:
Dpto. Electrónica, Tecnología de Computadoras y Proyectos, Universidad Politécnica de Cartagena, Cartagena, Spain;Dpto. Electrónica, Tecnología de Computadoras y Proyectos, Universidad Politécnica de Cartagena, Cartagena, Spain;Dpto. Electrónica, Tecnología de Computadoras y Proyectos, Universidad Politécnica de Cartagena, Cartagena, Spain;Dpto. Electrónica, Tecnología de Computadoras y Proyectos, Universidad Politécnica de Cartagena, Cartagena, Spain
Venue:
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
Year:
2005

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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.