Eyebrow Recognition by Comparison of Feature Strings

In order to study the novel biometric of eyebrow,this paper presents an eyebrow recognition method by comparison of feature strings,the basic idea of which is to extract feature strings using discrete Fourier transformation and K-means algorithm,and to recognize a given eyebrow image as the candidate person with the minimum edit distance between their feature strings.It has been shown that the method can reach an accuracy of 95.45% or 100.00% in six experiments on an small-scale eyebrow database taken from 22 persons.Therefore,eyebrow recognition may possibly apply to personal identification,which can be valid.