An Augmented Reality Visual Prothesis for People Affected by Tunneling Vision

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Abstract

An augmented reality based visual prothesis for people affected by tunnel vision is described in this paper. Using a head mounted display, useful information of the environment is superimposed on the own patient’s view, to enhance the user’s knowledge of the environment. That information is extracted by processing the images obtained from a camera. In order to provide versatility to the system and to accomplish the requirement of high performance, the image processing algorithm is performed with a cellular neural network, implemented on an FPGA device. The discrete CNN model proposed is derived from the continuous model, and details of its hardware implementation and the overall system architecture are reported.