Ear recognition based on compound structure classifier

Based on the research of ear recognition with independent component analysis (ICA), a new compound structure classifier (CSCER) ear recognition model was proposed. The model made rough classification to the human ears first according to their geometric features, then ICA was used to extract the algebra features and support vector machine (SVM) was for detailed classification, finally the results were achieved, which was in accordance with human natural recognition process. The model overcame the single ICA disadvantages of costing too much time and with too many features, also avoided losing structure feature when ear images were preprocessed. The experiment shows that the model can achieve high recognition rate and is suitable for complex ear image libraries.