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Analog VLSI implementation of the help if needed stereopsis algorithm

  • Rochester Institute of Technology

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

This brief introduces a novel clocked analog VLSI hardware system with an optical input that performs stereopsis. An algorithm called the Help If Needed Algorithm, developed previously, is readily mapped onto an analog VLSI platform. The system fits into the cellular neural network (CNN) paradigm. The circuit components that make up the cells of the CNN are designed with the constraint that they must function effectively and fit into the space available. In order to clarify the processing pathway, the system is described at the component and system levels. Each cell has an optical input, while the output is electrical. By utilizing an optical input, an analog VLSI silicon retina first stage can be connected to the stereopsis processor completely in parallel, creating a multi-stage artificial visual system. The physical system is composed of 2.0 μm Tinychips fabricated through MOSIS. Experimental data are presented that verify that the system performs as desired and successfully implements the Help If Needed Stereopsis Algorithm. The novel stereopsis processor is ideally suited for autonomous robots, or any application that requires a low power visual processing system.

Original languageEnglish
Pages (from-to)1328-1337
Number of pages10
JournalIEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing
Volume47
Issue number11
DOIs
StatePublished - Nov 2000

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