臺灣博碩士論文加值系統

本研究使用一般低成本的網路攝影機和可拓理論設計一套生物辨識系統，並期望能達到與市售高成本之生物辨識系統一樣之辨識效能。生物辨識系統中，可以擷取的特徵有很多種，在經濟成本考量和較能讓大眾所接受的是手部特徵；手部特徵可以分成三種，手部幾何、掌紋和指紋，不過每一個類型特徵都有它的優缺點。因此，本研究擷取兩種手部特徵-幾何和掌紋來辨識人的身分，兩種特徵可以相互補足彼此的缺點。文中手部幾何主要擷取手指的長度、寬度和輪廓特徵，掌紋主要擷取主線的長度、斜率和位置距離等特徵。本研究的辨識演算法利用可拓演算法來進行手部辨識，並與其他傳統演算法和辨識系統相互做比較，最後經由實驗結果得知，本研究所運用的方法擁有勝過傳統演算法的識別率，並進一步證實本文所設計之辨識系統性能並不亞於一般傳統示售的生物辨識系統。

This study used a low-cost webcam and extension theory to design a biometric system; it had a high recognition accuracy that is equivalent in high cost biometric system. There are many types of biological features that can be captured for biometric systems, the most economical and acceptable feature is hand feature. Features of hands can be divided into three categories, such as hand geometry, palm prints and fingerprints, and there are advantages and disadvantages in every single feature. Therefore, this paper used palm print and palm geometry. These two features can mutually complement each other's shortcomings. Hand geometry is to retrieve the finger length, width and profile characteristics, the palm print main captured length, slope and location of the main line distance. The recognition algorithm of this study used extension algorithm for the hand recognition, and was compared with other traditional algorithms and recognition systems. Finally, the experimental results show that the proposed method has higher recognition accuracy than traditional algorithms, and prove that low-cost biometric system has a high recognized accuracy, better than the traditional biometric system.

中文摘要 -------------------------------------------- I
英文摘要 ------------------------------------------- II
誌謝 --------------------------------------------- III
目錄 ----------------------------------------------- V
表目錄 --------------------------------------------- VII
圖目錄 -------------------------------------------- VIII
符號說明 ------------------------------------------- X
第一章 緒論---------------------------------------- 1
1.1 生物辨識技術簡介------------------------------ 1
1.2 研究動機-------------------------------------- 1
1.3 文獻回顧--------------------------------------- 2
1.4 論文大綱--------------------------------------- 4
第二章 影像擷取系統之架構------------------------ 6
2.1 影像擷取工具----------------------------------- 6
2.2 網路攝影機之優缺點------------------------------ 7
2.3 系統架構-------------------------------------- 7
第三章 手部影像特徵擷取之方法-------------------- 11
3.1 影像前處理階段--------------------------------- 11
3.2 手部的幾何部分--------------------------------- 11
3.2.1 最大類間發差法------------------------------- 11
3.2.2 手掌邊緣偵測--------------------------------- 13
3.2.3 手指端點定位--------------------------------- 15
3.3 手部的掌紋部分--------------------------------- 18
3.3.1 掌紋區域定位-------------------------------- 18
3.3.2 強化邊緣方法-------------------------------- 20
3.3.3 二值化方法---------------------------------- 21
3.3.4 去除雜訊方法--------------------------------- 21
3.3.5 線段化方法----------------------------------- 22
3.4 手部特徵擷取----------------------------------- 24
3.4.1 幾何特徵------------------------------------- 24
3.4.2 掌紋特徵------------------------------------ 26
第四章 手部辨識之方法------------------------------ 29
4.1 簡介----------------------------------------- 29
4.2 可拓理論-------------------------------------- 29
4.2.1 可拓集合-------------------------------- 30
4.2.2 物元理論------------------------------------ 32
4.2.3 可拓關聯函數-------------------------------- 33
4.3 可拓理論之評價方法----------------------------- 35
第五章 實驗結果和討論----------------------------- 42
5.1 實驗條件與數據-------------------------------- 42
5.1.1 實驗條件------------------------------------ 42
5.1.2 實驗數據------------------------------------ 42
5.2 實驗方法-------------------------------------- 53
5.3 實驗結果-------------------------------------- 56
5.4 實驗比較與探討--------------------------------- 60
第六章 結論與未來展望------------------------------ 63
6.1 結論------------------------------------ 63
6.2 未來展望--------------------------------- 64
參考文獻 ------------------------------------------ 65
作者簡介 ----------------------------------------- 71

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