A Robust Approach to Characterize the Human Ear: Application to Biometric Identification

Abstract

The Human ear is a new technology of biometrics which is not yet used in a real context or in commercial applications. For this purpose of biometric system, we present an improvement for ear recognition methods that use Elliptical Local Binary Pattern operator as a robust descriptor for characterizing the fine details of the two dimensional ear imaging. The improvements are focused on features extractions and dimensionalities reductions steps. The realized system is mainly appropriate for identification mode; it starts by decomposing the normalized ear image into several blocks with different resolutions. Next, the local textural descriptor is applied on each decomposed block. A problem of information redundancies is appeared due to the important size of the concatenated histograms of all blocks, which has been resolved by reducing of the histogram’s dimensionalities and by selecting the pertinent information using Haar Wavelets. Finally, the system is evaluated on the IIT Delhi Database containing two dimensional ear images and we have obtained a success rate about 97% for 493 images from 125 persons and about 96% for 793 images from 221 persons.