Complementary-reference and complementary-scene for real-time fingerprint verification using joint transform correlator

In this paper, a new configuration for the input joint images in the joint transform correlator is proposed for fast real-time binary characters and fingerprints verification. In the proposed scheme, the input joint image has a complementary-reference image and a complementary target image in addition to the reference and the target images. We use the cross-correlation peak value between the reference and the complementary target image and the cross-correlation peak value between the complementary reference and the target images as the criteria to perform the recognition of the target in the input scene. It is shown that these two cross-correlation peak values will be zero if and only if the input target matches the reference image. One advantage of using the proposed scheme is the elimination of the usual and necessary time-consuming normalization of the input images in the general correlation-based matching processes. Another advantage of the proposed scheme is the insensitive to light-sources intensity fluctuations that usually limits the matched-based recognition approaches. The scheme is employed to verify binary characters and fingerprints images; further, it is employed to verify occluded fingerprints target images on one hand, and to determine if a specific part or pattern exists in the target fingerprint image on the other hand.

[1]  Arun Ross,et al.  A hybrid fingerprint matcher , 2003, Pattern Recognit..

[2]  Y Zhang,et al.  Complementary-reference joint transform correlator. , 1994, Applied optics.

[3]  Katarzyna Chalasinska-Macukow,et al.  Wavelet transform for preprocessing in an optical correlator with a multilevel composite filter , 2004 .

[4]  Michael G. Strintzis,et al.  A 3D face and hand biometric system for robust user-friendly authentication , 2007, Pattern Recognit. Lett..

[5]  Arun Ross,et al.  An introduction to biometric recognition , 2004, IEEE Transactions on Circuits and Systems for Video Technology.

[6]  Joewono Widjaja,et al.  Real-time joint transform correlator using compressed reference images , 2004 .

[7]  B Javidi,et al.  Synthetic discriminant function-based binary nonlinear optical correlator. , 1989, Applied optics.

[8]  B. V. K. Vijaya Kumar,et al.  Spatial frequency domain image processing for biometric recognition , 2002, Proceedings. International Conference on Image Processing.

[9]  Mohammad S. Alam,et al.  Real-time fingerprint identification , 2004 .

[10]  Bahram Javidi,et al.  Experimental comparison of binary joint transform correlators used for fingerprint identification , 1996 .

[11]  B. Javidi,et al.  Binary nonlinear joint transform correlation with median and subset median thresholding. , 1991, Applied optics.

[12]  Mohammad S. Alam,et al.  Remove dc term and false alarms in fringe-adjusted joint transform correlator by using binary random phase mask , 2005 .

[13]  Mohammad S. Alam,et al.  Reference phase-encoded fringe-adjusted joint transform correlation , 2001 .

[14]  Anil K. Jain,et al.  Handbook of Fingerprint Recognition , 2005, Springer Professional Computing.

[15]  J. Goodman,et al.  A technique for optically convolving two functions. , 1966, Applied optics.

[16]  B. V. K. Vijaya Kumar,et al.  Incremental updating of advanced correlation filters for biometric authentication systems , 2003, 2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698).

[17]  Mohammad A. Karim,et al.  Joint transform correlator performance enhancement by a logarithmic-polar transformation , 1993 .

[18]  J P Barach,et al.  Faraday effect measurements with pulsed magnetic fields. , 1966, Applied optics.

[19]  J. Goodman.  Introduction to Fourier optics , 1969 .

[20]  J García,et al.  Coordinate-transformed filter for shift-invariant and scale-invariant pattern recognition. , 1997, Applied optics.

[21]  Jun Uozumi,et al.  Effects of threshold on single-target detection by using modified amplitude-modulated joint transform correlator , 2007 .

[22]  Jason Thornton,et al.  Using composite correlation filters for biometric verification , 2003, SPIE Defense + Commercial Sensing.

[23]  Marios Savvides,et al.  Robust shift-invariant biometric identification from partial face images , 2004, SPIE Defense + Commercial Sensing.

[24]  D. Casasent,et al.  Position, rotation, and scale invariant optical correlation. , 1976, Applied optics.

[25]  Yingzi Du,et al.  Biometric signal processing laboratory , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[26]  L A Romero,et al.  Normalized correlation for pattern recognition. , 1991, Optics letters.

[27]  Abdullah Bal,et al.  Improved fingerprint identification with supervised filtering enhancement. , 2005, Applied optics.

[28]  B. V. K. Vijaya Kumar,et al.  Performance of composite correlation filters in fingerprint verification , 2004 .

[29]  Hyeran Byun,et al.  Secure authentication system that generates seed from biometric information. , 2005, Applied optics.

[30]  J Levkovitz,et al.  Position-invariant, rotation-invariant, and scale-invariant process for binary image recognition. , 1997, Applied optics.

[31]  Venu Govindaraju,et al.  Symmetric hash functions for secure fingerprint biometric systems , 2007, Pattern Recognit. Lett..