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Design of semi-orthogonal wavelet for human ear recognition

Ear has robust as well as reliable features, thus technique have been proposed for ear detection and recognition from 2D & 3D ear images. In the proposed work, the ring projection technique is used to convert a 2-D ear image into 1-D information. This ring projection technique requires less memory for storage, and is rotation invariant. The 1-D information, after normalization, is used for the construction of the semi-orthogonal wavelet. Using the corresponding semi-orthogonal wavelet of each ear image, 2-D ear image is decomposed to two levels; thus energy compaction ratio for each ear image is obtained. The proposed approach is tested on USTB ear image database. The database contains three images of each subject are captured (total 180 images), under different lighting conditions. They all are right ear images of the subjects. Then variations of ECR value with the various obstructions (ear-ring or partial hair occlusion) in ear illustrate the amount of useful information contained by each image after decomposition using wavelet.