Abstract / Excerpt:

Biometrics is widely used nowadays for personal identification or verification based on physiological and biological features. In old times, biometrics were only used for signing on an agreements or for taking a prisoner’s identity by stamping its features, dipped on an ink, if it is a fingerprint for example, on a paper or on a document. Now, it is easy to acquire and it is unique for every individual. By using a biometric scanner, a biometric feature can easily be extracted and saved into a database, which can then be used for personal identification or authentication later on. There are various biometric features such as iris, fingerprint, face, palm print and etc., and among them, fingerprint is the most widely used biometric feature. Many access control systems adopt biometric features to replace digit­based password, which can be stolen in some cases or even be forgotten, to strengthen security or to promote privacy. In some cases, biometrics are implemented on laptops or computers to have a tighter security in logging in. By using this technology, this paper aims to provide an automated attendance monitoring system.

The research aims to develop an automated attendance system with the help of the palm print biometric features, not with the use a biometric scanner but with a camera. Using OpenCV/EmguCV, an open source computer vision and machine learning software library, to implement the image processes and algorithms in C# language.

For testing and evaluation, a live feed on a camera is processed in the application to detect or reject a match on an individual’s palm print. It should not detect a match if an individual’s palm print is not enrolled in the system.

Info

Source Institution	Ateneo de Davao University
Unit	Computer Studies
Authors	Paul David Conquilla
Page Count	14
Place of Publication	Davao City
Original Publication Date	March 1, 2015
Tags	Authentication Attendance, OpenCV, Palm Print

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