tailieunhanh - Multimodal biometric person authentication using fingerprint, face features

In this paper, the authors present a multimodal biometric system using face and fingerprint features with the incorporation of Zernike Moment (ZM) and Radial Basis Function (RBF) Neural Network for personal authentication. | Multimodal Biometric Person Authentication Using Fingerprint, Face Features Tran Binh Long1, Le Hoang Thai2, and Tran Hanh1 1 Department of Computer Science, University of Lac Hong 10 Huynh Van Nghe, DongNai 71000, Viet Nam tblong@ 2 Department of Computer Science, Ho Chi Minh City University of Science 227 Nguyen Van Cu, HoChiMinh 70000, Viet Nam lhthai@ Abstract. In this paper, the authors present a multimodal biometric system using face and fingerprint features with the incorporation of Zernike Moment (ZM) and Radial Basis Function (RBF) Neural Network for personal authentication. It has been proven that face authentication is fast but not reliable while fingerprint authentication is reliable but inefficient in database retrieval. With regard to this fact, our proposed system has been developed in such a way that it can overcome the limitations of those uni-modal biometric systems and can tolerate local variations in the face or fingerprint image of an individual. The experimental results demonstrate that our proposed method can assure a higher level of forge resistance in comparison to that of the systems with single biometric traits. Keywords: Biometrics, Personal Authentication, Fingerprint, Face, Zernike Moment, Radial Basis Function. 1 Introduction Biometrics refers to automatic identification of a person based on his physiological or behavioral characteristics [1],[2]. Thus, it is inherently more reliable and more capable in differentiating between an authorized person and a fraudulent imposter [3]. Biometric-based personal authentication systems have gained intensive research interest for the fact that compared to the traditional systems using passwords, pin numbers, key cards and smart cards [4] they are considered more secure and convenient since they can’t be borrowed, stolen or even forgotten. Currently, there are different biometric techniques that are either widely-used or under development, including face, facial .

• Vật lý
• Multimodal biometric person authentication
• The incorporation of Zernike Moment
• Radial Basis Function
• eural Network for personal authentication
• Single biometric traits