Ear Identification Method Based on High Discriminative Scale-Invariant Features
Feng Min · Journal of Southwest China Normal University · 2015
Efficient feature extraction is the key to improve the accuracy of recognition.The scale-invariant feature transform(SIFT)algorithm owns good invariance in the situation of affine transform,noise and a certain degree light strength changing;wavelet transform provides a sparse representation of a signal.It has been shown that it closely matches with the human perceptual system.In this paper,an ear identification method based on wavelet transform of the Scale-invariant feature transform features has been introduced.First,extract the SIFT features of human ear image.In addition,one-dimensional wavelet transform is applied to the SIFT feature vector to obtain more discriminative feature.At last,the cosine distance classifier is used for feature points matching and then complete recognition.Experimental results confirm that the high performance of the proposed method compared to some existing conventional methods.