Title :
Electronic Implementation of Biologically Inspired Neuromorphic Vision Sensor
Author :
Gangwar, D.S. ; Tiwari, Tarun ; Singh, Baldev
Author_Institution :
Dept. of ECE, GLAITM Mathura, Mathura
Abstract :
Neuromophic vision sensor is an electronic implementation of vision algorithm on semiconductor. Neuromophic systems are biologically inspired artificial neural systems that mimic algorithmic behavior of biological systems. The focus of this paper is to highlight photo transduction operation and conversion of optical information into the neuronal signal in the similar fashion as it takes place in biological retina. These systems have efficient adaptive and intelligent control techniques resembling with biological nervous system based on optical and electronic signal processing properties of semiconductor materials. Proposed electronic model contains adaptive photoreceptors as light sensors and other circuit components such as averaging circuits; circuits representing ganglion cells; neuronal firing circuits etc these entire elements junction to sense brightness, size, shape and orientation to distinguish objects in closer proximity. Neuromophic vision chip can lead towards development of sensory based artificial systems having parallel collective computation, adaptation, learning and memory implemented locally at each stage of processing of information.
Keywords :
adaptive control; image sensors; intelligent control; neural chips; adaptive control; adaptive photoreceptors; artificial neural systems; intelligent control; light sensors; neuromorphic vision sensor; photo transduction operation; Adaptive systems; Biological systems; Biomedical optical imaging; Biosensors; Circuits; Neuromorphics; Optical sensors; Optical signal processing; Retina; Signal processing algorithms; Adaptive Photo transduction; Algorithmic Behavior; Machine Vision; Neuromophic Systems; Vision Algorithm;
Conference_Titel :
Modeling & Simulation, 2008. AICMS 08. Second Asia International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-0-7695-3136-6
Electronic_ISBN :
978-0-7695-3136-6
DOI :
10.1109/AMS.2008.127