Analysis of feature extraction criteria for vector field visualization

G. Harikumar, Yoram Bresler

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper addresses the problem of the visualization of vector-valued images. It is attempted to synthesize a display matched to the capabilities of a human observer. The problem is reduced to the extraction of the best linear feature of the vector field. Several new nonparametric feature extraction criteria (Projection Indices) that make use of both the spatial and multivariate structures of the data have been recently proposed and demonstrated. A theoretical analysis of these projection indices and a Monte-Carlo study of their effectiveness is presented here. The study uses performance measures derived from a decision-theoretic model of the human observer.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Pattern Recognition
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages103-107
Number of pages5
ISBN (Electronic)0818662751
DOIs
StatePublished - 1994
Event12th IAPR International Conference on Pattern Recognition - Conference C: Signal Processing - Conference D: Parallel Computing, ICPR 1994 - Jerusalem, Israel
Duration: Oct 9 1994Oct 13 1994

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume3
ISSN (Print)1051-4651

Conference

Conference12th IAPR International Conference on Pattern Recognition - Conference C: Signal Processing - Conference D: Parallel Computing, ICPR 1994
Country/TerritoryIsrael
CityJerusalem
Period10/9/9410/13/94

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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