Geometric retrieval algorithm-based ear biometry with occluded images

Ear is a potential biometric parameter which has drawn the attention due to its structural uniqueness and stability over the age, obesity, disease, expression, etc., unlike other common biometric traits. In this work a geometric retrieval algorithm has been proposed for ear-based biometric analysis with occluded image. First the occlusion problem is countered by an empirical data driven technique and then PSO-based optimal features are extracted for comparison that reveals the authenticity of the subject with respect to a stored database. A search of minima from Euclidian distance-based analysis is used for final decision. The proposed system is tested on 50 subjects collected in multiple sessions in laboratory with a good recognition rate superior to similar reported works as indicated in the result section.