Information Fusion Methodology

Gerald M Flachs; Jay B Jordan; Jeffrey J Carlson

doi:10.1117/12.946648

9 August 1988 Information Fusion Methodology

Gerald M Flachs, Jay B Jordan, Jeffrey J Carlson

Proceedings Volume 0931, Sensor Fusion; (1988) https://doi.org/10.1117/12.946648
Event: 1988 Technical Symposium on Optics, Electro-Optics, and Sensors, 1988, Orlando, FL, United States

Abstract

An approach is presented for designing multisensor electronic vision systems using information fusion concepts. A random process model of the multisensor scene environment provides a mathematical foundation for fusing information. A complexity metric is introduced to measure the level of difficulty associated with various vision tasks. This complexity metric provides a mathematical basis for fusing information and selecting features to minimize the complexity metric. A major result presented in the paper is a method for utilizing a priori knowledge to fuse an n-dimensional feature vector X = (X1, X2, ..., Xn) into a single feature Y while retaining the same complexity. A fusing theorem is presented that defines the class of fusing functions that retains the minimum complexity.

Citation Download Citation

Gerald M Flachs, Jay B Jordan, and Jeffrey J Carlson "Information Fusion Methodology", Proc. SPIE 0931, Sensor Fusion, (9 August 1988); https://doi.org/10.1117/12.946648

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available