Principal Component Analysis of Thermal Dorsal Hand Vein Pattern Architecture

The quest of providing more secure identification system has lead to rise in developing biometric systems. Biometrics such as face, fingerprint and iris have been developed extensively for human identification purpose and also to provide authentic input to many security systems in the past few decades. Dorsal hand vein pattern is an emerging biometric which is unique to every individual. In this study principal component analysis is used to obtain Eigen vein patterns which are low dimensional representation of vein pattern features. The extraction of the vein patterns was obtained by morphological techniques. Noise reduction filters are used to enhance the vein patterns. Principle component analysis is able to reduce the 2-dimensional image database into 1-dimensional Eigen vectors and able to identify all the dorsal hand pattern images.

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