Latent Fingerprint and Vein Matching Using Ridge Feature Identification

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I. INTRODUCTION
Now a days, Biometrics maps to a new civilian applications of commercial use. Automatic Fingerprint Identification System(AFIS) appeared as an essential tool for all the biometrics and the law enforcement agencies[1].The demand of the secured biometric system, now lead to the growth in the features and individualities for the responsibility of quite complicated fingerprint and finger-vein present in the fingertips of the fingerprint. This important technology is widely used in area-access control, Pc login, and e-commerce. These all biometrics are attracted towards this technology, because of password theft, loss and release of user’s memory[10].
In biometrics system, the security and convenience of the system are important[10].The system requires high response times and fast accuracy. The biometrics includes the patterns based on fingerprint,fingervein,facial features,the iris, and the voice,hand grometry.However,some of the features are susceptible to forgery,so if it may used in conmbination the system will be efficient.The fingerprint and fingervein produces high confidentiality over other measures.
A. FINGERPRINT
In general,not even a twin sisters or twin brothers may not have the same fingerprint.They may be varying with respect to their genetic arrangements of cells and tissues. Fingerprint may consists of friction ridges and it is a combination of ridges(black line) and valleys(space between the two ridges).In fingerprint,level-2 fingerprint features has been executed with high performance and individuality in the fingerprints and it may produces the misperfections randomly in the case of friction ridges and they are known as the minutiae. These type of fingerprint acquisition typically utili...

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[9] M. Tico and P. Kuosmanen, “Fingerprint matching using and orientation based minutia descriptor,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 8, pp. 1009–1014, Aug. 2003
[10]Naoto Miura, Akio Nagasaka, Takafumi Miyatake, “ Feature extraction of finger-vein patterns based on repeated line tracking and its application to personal identification” Machine Vision and Applications ,Feb.2004
[11] R. Cappelli, M. Ferrara, and D. Maltoni, “Minutia cylinder-code: A new representation and matching technique for fingerprint recognition,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 32, no. 12, pp. 2128–2141, Dec. 2010.
[12] S. Yoon, J. Feng, and A. K. Jain, “Latent fingerprint enhancement via robust orientation field estimation,” in Proc. Int. Joint Conf. Biometrics, New Delhi, India, Oct. 2011, pp. 1–8.

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