Human ear recognition based on statistic features of local information
Jinyu Guo · Computer Engineering and Applications Journal · 2012
A new human ear recognition approach, based on statistic features of local information, is proposed. A human ear gray-scale image is divided into several sub-regions. The assorted features of each sub-regions are abstracted. Feature of sub-regions are joined in- to a feature vector to build human ear feature vector, thus gives a comprehensive description about the structure and local information of human ear images. The pattern classification is implemented by applying the nearest neighbor classifier. Three different feature extraction methods are adopted and USTB human ear database are applied to testing this algorithm. The experimental results show that the recognition rate is improved more than 30% compared with global information and the method based on statistics feature of local information is proved effective.