vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff3c32240000007908060001000400 In this paper, a multiwavelet based fingerprint compression technique using set partitioning in hierarchical trees (SPIHT) algorithm with optimised prefilter coefficients is proposed. While wavelet based progressive compression techniques give a blurred image at lower bit rates due to lack of high frequency information, multiwavelets can be used efficiently to represent high frequency information. SA4 (Symmetric Antisymmetric) multiwavelet when combined with SPIHT reduces the number of nodes during initialization to 1/4th compared to SPIHT with wavelet. This reduction in nodes leads to improvement in PSNR at lower bit rates. The PSNR can be further improved by optimizing the prefilter coefficients. In this work genetic algorithm (GA) is used for optimizing prefilter coefficients. Using the proposed technique, there is a considerable improvement in PSNR at lower bit rates, compared to existing techniques in literature. An overall average improvement of 4.23dB and 2.52dB for bit rates in between 0.01 to 1 has been achieved for the images in the databases FVC 2000 DB1 and FVC 2002 DB3 respectively. The quality of the reconstructed image is better even at higher compression ratios like 80:1 and 100:1. The level of decomposition required for a multiwavelet is lesser compared to a wavelet.
N R Rema1, K T Shanavaz2, P Mythili3
School of Engineering, Cochin University of Science & Technology, India1,3, College of Engineering, Kallooppara, India2
Multiwavelet, Fingerprint, Compression, Lower Bit Rate, Optimised Prefilter Coefficients
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| Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 8 , Issue: 1 , Pages: 1588-1595 )
Date of Publication :
August 2017
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201
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