Gradient based vein Extraction Algorithm for

In Present days, Authentication by means of biometrics systems is used for personal verifications. In spite of having existing technology in biometrics such as recognizing the fingerprints, voice/face recognition etc., the vein patterns can be used for the personal identification. Finger vein is a promising biometric pattern for personal identification and authentication in terms of its security and convenience. Finger vein has gained much attention among researchers to combine accuracy, universality and cost efficiency. We propose a method of personal identification based on finger-vein patterns. An image of a finger captured under infrared light contains not only the vein pattern but also irregular shading produced by the various thicknesses of finger bones and muscles. The proposed method extracts the finger-vein pattern from the unclear image by using gradient feature extraction algorithm and the template matching by Euclidean distance algorithm. The better vein pattern algorithm has to be introduced to achieve the better Equal Error Rate (EER) of 0.05 % comparing to the existing vein pattern recognition algorithms

Health Care Infrastructure Security using Bimodal

Abstract — Ensuring the security of patient medical record has become an important issue with this current l electronic medical record, this is due to the fact that patient confidential health information can be access, view and edit on Personal Computer (PC) at any time. In order to protect the patient health confidential information, this research use bimodal biometric (face and fingerprint) authentication to secure patient Electronic Medical Record (EMR). The bimodal biometric (fingerprint and face) are often affected by distortions which are caused by environmental noise such as oil, wrinkles, dry skin and dirt. These often affect the biometric system accuracy during authentication stage. In order to protect and improve the accuracy of patient Electronic medical Record (EMR) in health care infrastructure, this study introduced Modified Gabor Filter (MGF), a fast Principal Component Analysis (PCA) algorith