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Author: 林柏辰
Bo-chen Lin
Thesis Title: 基於區域性灰階尺度正規化的反射法靜脈辨識系統
Reflection Vein Recognition System Based on Local Gray-scale Normalization
Advisor: 洪西進
Shi-Jinn Horng
Committee: 林韋宏
Wei-hong Lin
Tzung-Wan Gau
Cheng-An Yen
Degree: 碩士
Department: 電資學院 - 資訊工程系
Department of Computer Science and Information Engineering
Thesis Publication Year: 2013
Graduation Academic Year: 101
Language: 中文
Pages: 44
Keywords (in Chinese): 生物辨識靜脈辨識特徵擷取反射法SURF
Keywords (in other languages): Biometrics, Vein recognition, Feature extraction, Reflection method, SURF
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  • 生物辨識是近幾年來相當重要的研究課題,生物辨識使用了人體上個體之間獨一無二的特徵進行辨識,像是最為廣泛使用的指紋辨識,還有人臉、虹膜、聲紋,而最近最為風行的則是靜脈辨識。靜脈辨識利用血液中血紅蛋白和其它人體組織對近紅外線的吸收率不同,讓靜脈紋理成像進行辨識。目前的靜脈辨識有使用手背、手掌及手指的靜脈進行辨識,而其中最普遍的則是手掌和手指靜脈。因為靜脈辨識是活體辨識,所以在偽造和造假的難度上是最高的,安全性也是最高的。

    Biometrics is a very important research topic in recent years. It is uses unique body feature between different people for identification. The most widely used such as fingerprint recognition, there are other like face, iris, voice, and the most popular of biometrics is vein identification. Vein identification is uses different near-infrared absorption rate of blood hemoglobin and other body tissues, make the vein texture appear for identification. Vein recognition is currently using back, palm and finger vein, the most common is the palm and finger vein. Vein recognition is vital identification so it’s very difficult to forge and fake, and it is also most secure.
    This paper will design a finger vein recognition system uses low-cost hardware, expected in the low-quality images can also have higher recognition results. Unlike the general finger vein recognition, this paper uses reflection method to capture vein image. First, decide the ROI from the capture image, then uses local gray-scale normalization for contrast enhancement, and then uses Sobel operator to enhance vein texture. Finally, use SURF for feature extraction and matching.

    摘要 I Abstract II 致謝 III 目錄 IV 表目錄 VI 圖目錄 VII 第一章 緒論 1 1.1 研究動機 1 1.2 研究目的 2 1.3 論文架構 3 第二章 靜脈辨識介紹與相關研究探討 5 2.1 靜脈辨識介紹 5 2.2 靜脈辨識相關研究 6 2.3 靜脈擷取機構介紹 8 第三章 系統架構 11 3.1 系統流程 11 3.2 系統操作介面介紹 13 第四章 研究方法與步驟 16 4.1 靜脈影像校正 16 4.2 靜脈影像前處理 19 4.3 擷取靜脈特徵影像 23 4.4 靜脈影像特徵擷取 23 4.5 靜脈影像特徵比對 35 第五章 實驗結果 37 5.1 開發環境 37 5.2 本實驗辨識結果 37 第六章 結論 39 參考文獻 41

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