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

Ti Chung Liu; Sunanda Mitra

doi:10.1117/12.243251

14 June 1996 Fingerprint recognition of wavelet-based compressed images by neuro-fuzzy clustering

Ti Chung Liu, Sunanda Mitra

Proceedings Volume 2761, Applications of Fuzzy Logic Technology III; (1996) https://doi.org/10.1117/12.243251
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

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.

Citation Download Citation

Ti Chung Liu and Sunanda Mitra "Fingerprint recognition of wavelet-based compressed images by neuro-fuzzy clustering", Proc. SPIE 2761, Applications of Fuzzy Logic Technology III, (14 June 1996); https://doi.org/10.1117/12.243251

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