IJCATR Volume 4 Issue 11

Fingerprint Image Compression using Sparse Representation and Enhancement with Wiener2 Filter

Divya Joseph Niya Joseph
10.7753/IJCATR0411.1012
keywords : Fingerprint Compression; Sparse Representation; Enhancement; Wiener2 Filter; Minutiae Extraction

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A technique for enhancing decompressed fingerprint image using Wiener2 filter is proposed. First compression is done by sparse representation. Compression of fingerprint is necessary for reducing the memory consumption and efficient transfer of fingerprint images. This is very essential for the application which includes access control and forensics. So the fingerprint image is compressed using sparse representation. In this technique, first dictionary is constructed for patches of fingerprint images. Then a fingerprint is selected and the coefficients are obtained and encoded. Thus the compressed fingerprint is obtained. But when the fingerprint is reconstructed, it is affected by noise. So Wiener2 filter is used to filter the noise in the image. The ridge and bifurcation count is extracted from decompressed and enhanced fingerprints. The experiment result shows that the enhanced fingerprint image preserves more bifurcation than decompressed fingerprint image. The future analysis can be considered for preserving ridges.
@artical{d4112015ijcatr04111012,
Title = "Fingerprint Image Compression using Sparse Representation and Enhancement with Wiener2 Filter",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "4",
Issue ="11",
Pages ="860 - 864",
Year = "2015",
Authors ="Divya Joseph Niya Joseph"}
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