A novel technique for palmprint classification and authentication

Palmprint database is categorised into two groups, right hand group and left hand group and then each group is classified based on principal line i.e., Heart Line. A rectangular Region of Interest (ROI), in which only heart line is present, is extracted for classification, which is divided into six regions and the palmprint database is classified based on the regions that the heart line traverses in the palm. ROI is extracted for the authentication, using this, techniques like filiformity to extract the line like features and Gabor filter to extract texture features from the palm are used. Performance of the two techniques determined individually. A sum rule is applied to combine the features obtained from the two techniques to develop an intramodel system. Fusion is applied at both feature level as well as matching score level for the authentication mechanism.