Personal Authentication Based on Curvelet Transform of Palm Print Moments

Image transformation provide deep meaning about images feature, so many type of image are appear in the last decade years, one them is curvelet which improve processing techniques specially field feature extraction. Personal authentication adopt biometric information to be major coefficients this field.
 Palm print main approaches for personal identification. So studying moments extracted from transform palm adopted order get high efficient system personalization systems. Two phases constructed research low frequency coefficient In first phase a database was built 50 persons by acquisition nine both hands (9 left hand and 9for right hand). acquired then processed extract ROI (region interest) looking centroid square shape will fixed based on that centroid. This preprocess play an important step stable features. Histogram applied apply SOBLE operator morphological operation highlight features print, decomposition each transformation. Select (which hold details). Evaluation seven (18images) store there file (so person have 126 values), called preparation. While second detection phase, same steps evaluate as done go through closest tested one.
 System evaluation measured statistical metrics show good result goes up 96% when with different conditions. Also effect dimension individual integrated studied, yield recommended 192*192.