On the existence of complete invariant feature spaces in pattern recognition

2 January 2003

conference paper
Published by Institute of Electrical and Electronics Engineers (IEEE)

p. 178-182
https://doi.org/10.1109/icpr.1992.201749

Abstract

This paper presents a general and model-independent analysis of the problem of feature extraction in pattern recognition. Two criteria are derived which ensure the existence of a complete feature space. This is a space which contains exactly the information relevant for the classification process following feature extraction. Several possibilities for the construction of such a complete feature space are discussed and experimental results which indicate the potential of the proposed methods for practical applications are presented.

Keywords

PATTERN RECOGNITION
FEATURE EXTRACTION
PATTERN ANALYSIS
PATTERN CLASSIFICATION
DATA MINING
SIGNAL MAPPING
INFORMATION FILTERING
INFORMATION FILTERS
SUFFICIENT CONDITIONS
SIGNAL GENERATORS

This publication has 2 references indexed in Scilit:

Modified rapid transform
Applied Optics, 1989
Geometrische Methoden in der Invariantentheorie
Published by Springer Nature ,1984