Fingerprint recognition of wavelet-based compressed images by neuro-fuzzy clustering

T. C. Liu, Sunanda Mitra

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

1 Scopus citations

Abstract

Image compression plays a crucial role in many important and diverse applications requiring efficient storage and transmission. This work mainly focuses on a wavelet transform (WT) based compression of fingerprint images and the subsequent classification of the reconstructed images. The algorithm developed involves multiresolution wavelet decomposition, uniform scalar quantization, entropy and run- length encoder/decoder and K-means clustering of the invariant moments as fingerprint features. The performance of the WT-based compression algorithm has been compared with JPEG current image compression standard. Simulation results show that WT outperforms JPEG in high compression ratio region and the reconstructed fingerprint image yields proper classification.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsBruno Bosacchi, James C. Bezdek
Pages76-86
Number of pages11
StatePublished - 1996
EventApplications of Fuzzy Logic Technology III - Orlando, FL, USA
Duration: Apr 10 1996Apr 12 1996

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume2761

Conference

ConferenceApplications of Fuzzy Logic Technology III
CityOrlando, FL, USA
Period04/10/9604/12/96

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