Reliable user authentication is becoming an increasingly important task in the Web-enabled world. The consequences of an insecure authentication system in a corporate or enterprise environment can be catastrophic, and may include loss of confidential information, denial of service, and compromised data integrity. The value of reliable user authentication is not limited to just computer or network access. Palmprint authentication is regarded as one of the efficient biometric trait. Palm consists of the reliable features like palm lines, ridges, texture, etc. Before extracting the features, we need to pre-process and segment the image to obtain the Region of Interest (ROI). While capturing the palm image we also get the fingers and other parts like wrist etc., Segmentation of the palm region from the captured image is an important step before extracting the features. Here texture features are being extracted. They consist of wrinkles, which are different from principle lines in that they are thinner and more irregular.
Texture features are being extracted using a technique, namely 2D-Log Gabor filter which has been used to extract the Iris features earlier. Same method can be applied to extract palmprint features and False acceptance rate as well as Genuine acceptance rate can be calculated to evaluate the performance of the biometric system.
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