Paper Information

Journal:   IRANIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING (IJECE)   SUMMER-FALL 2007 , Volume 6 , Number 2; Page(s) 133 To 140.
 
Paper: 

FINGERPRINT COMPRESSION USING CONTOURLET TRANSFORM AND SELF ORGANIZING FEATURE MAP

 
 
Author(s):  VEERAKUMAR T., SUDHAKAR R., ESAKKIRAJAN S., SENTHIL MURUGAN V.
 
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Abstract: 

This paper presents a new coding technique for fingerprint compression, which is based on contourlet transform and Self-Organizing Feature Map (SOFM) vector quantization. One of the main difficulties in developing compression algorithms for fingerprints resides in the need for preserving the minutiae, which are subsequently used in identification. Wavelets have shown their ability in representing natural images that contain smooth areas separated with edges. However, wavelets cannot efficiently represent the ridge and furrow patterns, which are predominant in fingerprints. This issue is addressed by directional transforms, known as contourlets, which have the property of preserving edges. SOFM based vector quantizer quantizes the coefficients obtained by contourlet transform. The results obtained are tabulated and compared with those of the wavelet based ones.

 
Keyword(s): CONTOURLET TRANSFORM, DIRECTIONAL FILTER BANK, LAPLACIAN PYRAMID, SELF ORGANIZING FEATURE MAP
 
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