چکیده (انگلیسی):

Ear recognition is a new technology and future trend for personal identification. However, the false detection
rate and matching recognition are very challenging due to the ear complex geometry. The Scope of the study is
to introduced a combination of Iterative Closest Point (ICP) and Stochastic Clustering Matching (SCM)
algorithm for 3D ears matching based on biometrics field with a good steadiness to reduce the false detection
rate. The corresponding ear extracts from the side range image and characterized by 3D features. The proposed
method used matlab simulation and defined the average detection time 35ms and an identification similarity is
98.25% for the collection of different database. The result shows that the proposed combined method
outperforms than the existing of ICP or SCM in terms of detection time and accuracy in training.