Ear recognition using a hybrid approach based on neural networks

The purpose of this paper is to offer a combined approach in biometrics analysis field integrating some of the most known techniques using ears to recognize people. This study uses Hausdorff distance as a pre-processing stage adding sturdiness to increase the performance filtering for the subjects to use it in the testing process. Also includes the Image Ray Transform (IRT) and the Haar based classifier for the detection step. Then, the system computes SURF and LDA features as an input of two neural networks to recognize a person by the patterns of its ear. To show the applied theory experimental results, the above algorithms have been implemented using the programming language Microsoft C#. The investigation results showed robustness improving the ear recognition process.