Multi-chip implementation of a biomimetic VLSI vision sensor based on the Adelson-Bergen algorithm

Erhan Ozalevli, Charles M. Higgins

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Scopus citations

Abstract

Biological motion sensors found in the retinas of species ranging from flies to primates are tuned to specific spatio-temporal frequencies to determine the local motion vectors in their visual field and perform complex motion computations. In this study, we present a novel implementation of a silicon retina based on the Adelson-Bergen spatio-temporal energy model of primate cortical cells. By employing a multi-chip strategy, we successfully implemented the model without much sacrifice of the fill factor of the photoreceptors in the front-end chip. In addition, the characterization results proved that this spatio-temporal frequency tuned silicon retina can detect the direction of motion of a sinusoidal input grating down to 10 percent contrast, and over more than a magnitude in velocity. This multi-chip biomimetic vision sensor will allow complex visual motion computations to be performed in real-time.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsOkyay Kaynak, Ethem Alpaydin, Erkki Oja, Lei Xu
PublisherSpringer-Verlag
Pages433-440
Number of pages8
ISBN (Print)3540404082, 9783540404088
DOIs
StatePublished - Jan 1 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2714
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Ozalevli, E., & Higgins, C. M. (2003). Multi-chip implementation of a biomimetic VLSI vision sensor based on the Adelson-Bergen algorithm. In O. Kaynak, E. Alpaydin, E. Oja, & L. Xu (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 433-440). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2714). Springer-Verlag. https://doi.org/10.1007/3-540-44989-2_52