%0 Journal Article %1 ravijgeethaks2011bimodal %A Ravi J, Geetha K S, Anitha T N %A Raja, K B %D 2011 %E Das, Dr. Vinu V %J International Journal on Information Technology %K DCT DWT Euclidean_distance FFT Fingerprint Iris %N 3 %P 6 %T Bimodal Biometric System using Multiple Transformation Features of Fingerprint and Iris %U http://doi.searchdl.org/01.IJIT.1.3.559 %V 1 %X The biometric technology is used to identify individuals effectively compared to existing traditional methods. In this paper we propose Bimodal Biometric System using Multiple Transformation features of Fingerprint and Iris (BBMFI). The iris image is preprocessed to generate iris template. The two level Discrete Wavelet Transformation (DWT) is applied on iris template and Discrete Cosine Transformation (DCT) is performed on second level low frequency band to generate DCT coefficients which results in features of iris. The fingerprint is preprocessed to obtain Region of Interest (ROI) and segmented into four cells. Then the DWT is applied on each cell to derive approximation band and detailed bands. The Fast Fourier Transformation (FFT) is applied on approximation band to compute absolute values that results in features of fingerprint. The iris features and fingerprint features are fused by concatenation to obtain final set of features. The final feature vector of test and database are compared using Euclidean distance matching. It is observed that the values of Total Success Rate (TSR), False Rejection Rate (FRR) and False Acceptance Rate (FAR) are improved in the proposed system compared to existing algorithm.

@article{ravijgeethaks2011bimodal, abstract = {The biometric technology is used to identify individuals effectively compared to existing traditional methods. In this paper we propose Bimodal Biometric System using Multiple Transformation features of Fingerprint and Iris (BBMFI). The iris image is preprocessed to generate iris template. The two level Discrete Wavelet Transformation (DWT) is applied on iris template and Discrete Cosine Transformation (DCT) is performed on second level low frequency band to generate DCT coefficients which results in features of iris. The fingerprint is preprocessed to obtain Region of Interest (ROI) and segmented into four cells. Then the DWT is applied on each cell to derive approximation band and detailed bands. The Fast Fourier Transformation (FFT) is applied on approximation band to compute absolute values that results in features of fingerprint. The iris features and fingerprint features are fused by concatenation to obtain final set of features. The final feature vector of test and database are compared using Euclidean distance matching. It is observed that the values of Total Success Rate (TSR), False Rejection Rate (FRR) and False Acceptance Rate (FAR) are improved in the proposed system compared to existing algorithm.}, added-at = {2012-09-24T06:46:15.000+0200}, author = {{Ravi J, Geetha K S}, Anitha T N and Raja, K B}, biburl = {https://www.bibsonomy.org/bibtex/24b907beb9e7cea1e3553af74152b2c34/ideseditor}, editor = {Das, Dr. Vinu V}, interhash = {7610c693840729760f47627635eae084}, intrahash = {4b907beb9e7cea1e3553af74152b2c34}, journal = {International Journal on Information Technology}, keywords = {DCT DWT Euclidean_distance FFT Fingerprint Iris}, month = {December}, number = 3, pages = 6, timestamp = {2012-09-24T06:46:15.000+0200}, title = {Bimodal Biometric System using Multiple Transformation Features of Fingerprint and Iris}, url = {http://doi.searchdl.org/01.IJIT.1.3.559}, volume = 1, year = 2011 }