Two-dimensional signal classification by multiscale wavelet representation

Hamed Sari-Sarraf, Dragana Brzakovic

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

This paper describes a technique for classification of 2-D discrete signals. It consists of four modules, namely the partition, representation, measurement, and the classification modules. The first of these either passes the observed signal as a whole or divides it into subregions which may or may not overlap. The representation module first computes the shift-invariant multiscale wavelet representations (MSWAR) of the reference and the observed signals and then generates a corresponding set of 1-D signatures. The measurement module extracts those vital signal features to which the decision rules of the classification module are applied. The paper presents the design and implementation of each of these modules, emphasizing theoretical background behind the design and efficiency of their implementation. Also some preliminary results have been included that demonstrate the ability of this technique to classify observed signals that are corrupted by different types of deformities.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherPubl by Int Soc for Optical Engineering
Pages406-417
Number of pages12
ISBN (Print)081940943X, 9780819409430
DOIs
StatePublished - 1992
EventAdvanced Signal Processing Algorithms, Architectures, and Implementations III - San Diego, CA, USA
Duration: Jul 19 1992Jul 21 1992

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume1770
ISSN (Print)0277-786X

Conference

ConferenceAdvanced Signal Processing Algorithms, Architectures, and Implementations III
CitySan Diego, CA, USA
Period07/19/9207/21/92

Fingerprint

Dive into the research topics of 'Two-dimensional signal classification by multiscale wavelet representation'. Together they form a unique fingerprint.

Cite this