Ear description and recognition using ELBP and wavelets

The human ear is a new technology in 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 technique for characterizing the fine details of the two dimensional ear images. The improvements are focused on feature extraction and dimensionality reduction steps. The realized system is mainly appropriate for verification mode; it starts by decomposing the normalized ear image into several blocks with different resolutions. Next, the 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 of 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 94% for 500 images from 100 persons.