A new ear recognition approach, including a feature extraction method and the recognition framework, is presented in this paper. The proposed feature extraction method, called the Local Similarity Binary Pattern (LSBP), considers both the connectivity and similarity information in representation. In ear recognition, LSBP is combined with the Local Binary Pattern (LBP) to represent the ear image. The concatenated histogram sequences encode more relationships among neighborhoods that are shown to be discriminative. To enhance efficient representation, Cellular Neural Network is adopted to preprocess images, the function of which is to eliminate irrelevant information. From the experimental results conducted on the USTB ear database, the proposed approach outperforms some other well-known methods in terms of the recognition rate.
This new method, which is used in conjunction with the Local Binary Pattern (LBP) features, is found to have superior ear recognition performance REF .
Ear recognition using a new local matching approach
2008 15th IEEE International Conference on Image Processing
2008 15th IEEE International Conference on Image Processing
Computer Science