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研究生: 李定家
Lee, Ting-Chia
論文名稱: 手機平台活體偵測與身份認證機制設計
Design of Liveness Detection and Identity Recognition System for Mobile Phone
指導教授: 胡敏君
Hu, Min-Chun
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年: 2019
畢業學年度: 107
語文別: 英文
論文頁數: 54
中文關鍵詞: 生物辨識防偽機制使用者認證UI設計
外文關鍵詞: biometrics identification, anti-spoofing mechanism, user authentication, UI design
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  • 網路的崛起,產生了各種新穎的服務,數位金融這項方便的服務也隨之而來,透過網路轉帳繳款已經不是空談,但資訊安全仍然是一大問題,各種加密措施為了保護使用者資訊紛紛被設計出來,為了提升帳戶安全度,各家銀行也增加使用者帳號密碼的限制,雖然多少有效,但同時也增加了使用者的不便。因此生物辨識技術便開始發達,透過生物特徵與認證系統結合,從每個人的生理特徵尋找微小的差異處,是生物辨識的精神,但能做到如此細緻功能的技術同時也需要高端的硬體,立體臉部辨識的紅外線攝影機、指紋辨識個掃描器或是虹膜辨識的高畫質相機,無一不是成本高昂。本論文致力於將只需要單顆彩色相機鏡頭的平面臉部辨識與使用者認證系統結合,設計出與使用者互動的方式排除影像及影片偽造行為,在手機上同時達到安全又有效率之功能。

    The rise of the Internet has produced a variety of innovative services. The convenient service of Fintech has followed. It is no longer a dream about payment or transferring through Internet, but information security is still a big problem. Various encryption measure shave been designed to protect user information. In order to improve account security, banks have also increased the restrictions on user account passwords. Although it is effective, it also increases user inconvenience. Therefore, biometrics identification has begun to develop. The spirit of biometric identification is combining biometrics and authentication systems to find small differences from each person’s physiological characteristics. However, technologies that can achieve such meticulous functions also require high-end hardware. Infrared cameras with stereo face recognition, fingerprint recognition scanners or high-resolution cameras with iris recognition are all costly. This paper is dedicated to combining the flat face recognition that requires only a single color camera with the user authentication system, and designing a way of interacting with the user to eliminate image and film spoofing, and achieve safe and efficient functions on the mobile phone at the same time.

    摘要......i Abstract......ii Acknowledgements......iii Table of Contents......v List of Tables......vii List of Figures......viii Chapter 1. Introduction...1 Chapter 2. Related Work...4 2.1 Identity Recognition. . . . . . . . . . . . . . . . . . . . . . . . . . . .4 2.1.1 Biometric Identification. . . . . . . . . . . . . . . . . . . . . .4 2.1.2 Face recognition. . . . . . . . . . . . . . . . . . . . . . . . . .7 2.2 Liveness Detection. . . . . . . . . . . . . . . . . . . . . . . . . . . . .8 2.2.1 Face Landmark Estimation. . . . . . . . . . . . . . . . . . . . .9 2.3 Tensorflow.js Introduction. . . . . . . . . . . . . . . . . . . . . . . . .10 2.4 User Identification Mechanism. . . . . . . . . . . . . . . . . .11 Chapter 3. System Framework.....13 3.1 Registration System. . . . . . . . . . . . . . . . . . . . . . . . . . . .13 3.2 Login System. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15 3.3 Function Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . .17 3.3.1 Face Detector. . . . . . . . . . . . . . . . . . . . . . . . . . . .17 3.3.2 Feature Extractor. . . . . . . . . . . . . . . . . . . . . . . . . .18 3.3.3 Liveness Detector. . . . . . . . . . . . . . . . . . . . . . . . . .20 3.3.4 Identification. . . . . . . . . . . . . . . . . . . . . . . . . . . .21 3.3.5 Liveness Matcher. . . . . . . . . . . . . . . . . . . . . . . . . .23 Chapter 4. Experimental Results.....24 4.1 Objective Evaluation. . . . . . . . . . . . . . . . . . . . . . . . . . . .24 4.1.1 Face Recognize Comparison. . . . . . . . . . . . . . . . . . . .24 4.1.2 Face Landmark Comparison. . . . . . . . . . . . . . . . . . . .26 4.1.3 Tensorflow.js Evaluation. . . . . . . . . . . . . . . . . . . . . .27 4.1.4 System Accuracy and Efficiency Evaluation. . . . . . . . .28 4.2 Subjective Evaluation. . . . . . . . . . . . . . . . . . . . . . . . . . .32 4.2.1 User Interface Operation Evaluation. . . . . . . . . . . . . .32 4.2.2 Qualitative Questionnaire Analysis and Improvement...34 4.2.3 System Usability and Accuracy Evaluation.. . . . . . . . .37 Chapter 5. Conclusions and Future Work....47 References...48

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