Fingerprint Compression Using Contourlet Transform and Multistage Vector Quantization

Authors: S. Esakkirajan, T. Veerakumar, V. Senthil Murugan, R. Sudhakar

Abstract:

This paper presents a new fingerprint coding technique based on contourlet transform and multistage vector quantization. Wavelets have shown their ability in representing natural images that contain smooth areas separated with edges. However, wavelets cannot efficiently take advantage of the fact that the edges usually found in fingerprints are smooth curves. This issue is addressed by directional transforms, known as contourlets, which have the property of preserving edges. The contourlet transform is a new extension to the wavelet transform in two dimensions using nonseparable and directional filter banks. The computation and storage requirements are the major difficulty in implementing a vector quantizer. In the full-search algorithm, the computation and storage complexity is an exponential function of the number of bits used in quantizing each frame of spectral information. The storage requirement in multistage vector quantization is less when compared to full search vector quantization. The coefficients of contourlet transform are quantized by multistage vector quantization. The quantized coefficients are encoded by Huffman coding. The results obtained are tabulated and compared with the existing wavelet based ones.

Keywords: Contourlet Transform, Directional Filter bank, Laplacian Pyramid, Multistage Vector Quantization

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1069929

References:

[1] Pennebaker W.B. and Mitchell J.L, JPEG-Still Image Data Compression Standards. Van Nostrand Reinhold, 1993.
[2] C.M. Brislawn, J.N. Bradley and R.J. Onyschczak and T. Hopper, "The FBI Compression Standard for Digitized Fingerprint Images," in 1996 Proc. SPIE, vol.2847, pp. 344-355.
[3] M.Antonini, M.Barlaud, P. Mathieu, and I.Daubechies, "Image coding using wavelet transform," IEEE Trans. Image Proc, pp.205-220, Apr.1992.
[4] M. N. Do and M. Vetterli, "The contourlet transform: an efficient directional multiresolution image representation," IEEE Trans. Of Image Processing, vol.14, no.12, pp. 2091-2106, Dec. 2004.
[5] B.H.Juang and A.H.Gray, "Multiple stage vector quantization for speech coding," in 1982 Proc. IEEE Int.Conf.Acoust, Speech, Signal Processing (Paris, France), pp.597-600.
[6] K.P. Soman and K.I. Ramachandran, Insight into Wavelets from Theory to Practice, Prentice Hall India, New Delhi, 2002, ch.9.
[7] A.Gersho and R.M. Gray, Vector Quantization and Signal Compression. Boston, MA: Kluwer, 1992.
[8] M. N. Do and M.Vetterli, "Pyramidal directional filter banks and curvelets," in 2001 Proc. Of IEEE Int. Conf. on Image Proc, vol.3, pp.158-161, Thessaloniki, Greece.
[9] D.D. Y. Po and M. N. Do, "Directional multiscale modeling of images using the contourlet transform," IEEE Trans. on Image Processing, to appear, Jun. 2006.
[10] P. J. Burt and E. H. Adelson, "The Laplacian pyramid as a compact image code," IEEE Trans. on Commun. vol. 31, no. 4, pp. 532-540, 1983.
[11] M. N. Do, "Directional Multiresolution Image Representations," Ph.D.Thesis, EPFL, Lausanne, Switzerland, Dec. 2001.
[12] R. H. Bamberger and M. J. T. Smith, "A filter bank for the Directional decomposition of images: theory and design," IEEE Trans. on Signal Processing, vol. 40, no. 4, pp. 882-893, Apr. 1992.
[13] Jayshree Karlekar, P.G. Poonacha and U.B. Desai, "Image Compression using Zerotree and Multistage Vector Quantization", ICIP, Vol.2, pp.610, 1997.
[14] Hosam Khalil, Kenneth Rose, "Multistage vector quantizer optimization for packet networks," IEEE Trans. Signal Proc. Vol. 51, No.7, pp.1870- 1879, July 2003.
[15] Y. Linde, A. Buzo and R.M.Gray, "An algorithm for vector quantizer design," IEEE Trans. Commun. Vol.28, pp.84-95, Jan.1980.
[16] R. Sudhakar, R. Karthiga and S. Jayaraman, "Fingerprint compression using Contourlet Transform with Modified SPIHT algorithm", IJECE, vol.5, No.1, pp.3-10, Winter-Spring 2006.
[17] www.biometrics.cse.msu.edu/fingerprint.html.