关键词: 手写签名鉴别, Contourlet, 特征提取, 支持向量机

Abstract: Handwritten Signature Verification（HSV） is a discipline which aims to validate the identity of writers according to the handwriting styles.Compared with on-line HSV，off-line HSV is less limited in equipment involvement and can be applied in more fields.Nevertheless，it is more difficult to manipulate than on-line HSV due to the loss of dynamic information during the writing process.This paper focuses on off-line HSV and presents a new feature selection method based on Contourlet，which gives full play to the merits of both conventional structure feature and statistical feature.After dimensionality reduction to extracted eigenvector by K-L transform，genuine signatures and forgeries are distinguished through Support Vector Machines（SVM）.The result of the experiment has confirmed the effectiveness of the proposed approach.

Key words: Handwritten Signature Verification（HSV）, Contourlet, feature extraction, Support Vector Machine（SVM）