Abstract: The quest of providing more secure identification
system has led to a rise in developing biometric systems. Dorsal
hand vein pattern is an emerging biometric which has attracted the
attention of many researchers, of late. Different approaches have
been used to extract the vein pattern and match them. In this work,
Principle Component Analysis (PCA) which is a method that has
been successfully applied on human faces and hand geometry is
applied on the dorsal hand vein pattern. PCA has been used to obtain
eigenveins which is a low dimensional representation of vein pattern
features. Low cost CCD cameras were used to obtain the vein
images. The extraction of the vein pattern was obtained by applying
morphology. We have applied noise reduction filters to enhance the
vein patterns. The system has been successfully tested on a database
of 200 images using a threshold value of 0.9. The results obtained are
encouraging.