Biologically Inspired Vision Sensor for the Detection of Higher-Level Image Features

Loading...
Thumbnail Image

Embargo Date

Related Collections

Degree type

Discipline

Subject

vision sensor
smart sensor
image features
biologically inspired
CNN

Funder

Grant number

License

Copyright date

Distributor

Related resources

Author

Nishimura, Masatoshi

Contributor

Abstract

The paper briefly reviews certain aspects of the biological visual system and presents a smart vision sensor for the detection of higher-level features. The visual system processes information in a hierarchical manner starting from the retina up to the visual cortex. It decomposes the image in simple features (edges, orientation, line stops, corners, etc) using spatial and temporal information. At the higher level it integrates these primitive features, resulting in the recognition of complex objects. The sensor described in the paper is loosely modeled after the visual system and incorporates pixel level, programmable elements which extract orientation, end stops, corners and junctions from a line drawing. The architecture resembles a CNN-UM that can be programmed with a 30-bit word. The 16 x 16 pixels array detects these higher-level features in about 54 μseconds.

Advisor

Date of presentation

2003-12-16

Conference name

Departmental Papers (ESE)

Conference dates

2023-05-16T21:44:20.000

Conference location

Date Range for Data Collection (Start Date)

Date Range for Data Collection (End Date)

Digital Object Identifier

Series name and number

Volume number

Issue number

Publisher

Publisher DOI

Journal Issues

Comments

Copyright 2003 IEEE. Reprinted from Proceedings of the 2003 IEEE Conference on Electron Devices and Solid-State Circuits, pages 11-16. Publisher URL: http://ieeexplore.ieee.org/xpl/tocresult.jsp?isNumber=28656 This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

Recommended citation

Collection