Feature selection and decision space mapping for sensor fusion

Cynthia L. Beer; Gerald M. Flachs; David R. Scott; Jay B. Jordan

doi:10.1117/12.969978

Feature selection and decision space mapping for sensor fusion

Cynthia L. Beer, Gerald M. Flachs, David R. Scott, Jay B. Jordan

Informatics, Computing, and Cyber Systems, School of

Research output: Contribution to journal › Article › peer-review

Abstract

An information fusion approach is presented for mapping a multiple dimensional feature space into a lower dimensional decision space with simplified decision boundaries. A new statistic, called the tie statistic, is used to perform the mapping by measuring differences in probability density functions of features. These features are then evaluated based on the separation of the decision classes using a parametric beta representation for the tie statistic. The feature evaluation and fusion methods are applied to perform texture recognition.

Original language	English (US)
Pages (from-to)	223-234
Number of pages	12
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	1198
DOIs	https://doi.org/10.1117/12.969978
State	Published - Mar 1 1990

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

Access to Document

10.1117/12.969978

Cite this

@article{fe0370d42b15421facf74bbcdc6dd516,

title = "Feature selection and decision space mapping for sensor fusion",

abstract = "An information fusion approach is presented for mapping a multiple dimensional feature space into a lower dimensional decision space with simplified decision boundaries. A new statistic, called the tie statistic, is used to perform the mapping by measuring differences in probability density functions of features. These features are then evaluated based on the separation of the decision classes using a parametric beta representation for the tie statistic. The feature evaluation and fusion methods are applied to perform texture recognition.",

author = "Beer, {Cynthia L.} and Flachs, {Gerald M.} and Scott, {David R.} and Jordan, {Jay B.}",

year = "1990",

month = mar,

day = "1",

doi = "10.1117/12.969978",

language = "English (US)",

volume = "1198",

pages = "223--234",

journal = "Proceedings of SPIE - The International Society for Optical Engineering",

issn = "0277-786X",

publisher = "SPIE",

}

TY - JOUR

T1 - Feature selection and decision space mapping for sensor fusion

AU - Beer, Cynthia L.

AU - Flachs, Gerald M.

AU - Scott, David R.

AU - Jordan, Jay B.

PY - 1990/3/1

Y1 - 1990/3/1

N2 - An information fusion approach is presented for mapping a multiple dimensional feature space into a lower dimensional decision space with simplified decision boundaries. A new statistic, called the tie statistic, is used to perform the mapping by measuring differences in probability density functions of features. These features are then evaluated based on the separation of the decision classes using a parametric beta representation for the tie statistic. The feature evaluation and fusion methods are applied to perform texture recognition.

AB - An information fusion approach is presented for mapping a multiple dimensional feature space into a lower dimensional decision space with simplified decision boundaries. A new statistic, called the tie statistic, is used to perform the mapping by measuring differences in probability density functions of features. These features are then evaluated based on the separation of the decision classes using a parametric beta representation for the tie statistic. The feature evaluation and fusion methods are applied to perform texture recognition.

UR - http://www.scopus.com/inward/record.url?scp=0024779584&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0024779584&partnerID=8YFLogxK

U2 - 10.1117/12.969978

DO - 10.1117/12.969978

M3 - Article

AN - SCOPUS:0024779584

SN - 0277-786X

VL - 1198

SP - 223

EP - 234

JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

ER -

Feature selection and decision space mapping for sensor fusion

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this