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研究生: 黃武龍
Wu-lung Huang
論文名稱: 利用影像切割法來設計指靜脈影像處理介面
Implementation of Finger Vein Image Process using Image Segmentation
指導教授: 李柏磊
Po-lei Lee
口試委員:
學位類別: 碩士
Master
系所名稱: 資訊電機學院 - 電機工程學系在職專班
Executive Master of Electrical Engineering
畢業學年度: 100
語文別: 中文
論文頁數: 61
中文關鍵詞: 微處理器手指靜脈血管影像處理影像切割
外文關鍵詞: Microprocessor, Finger Vein, Image Processing, Image Segmentation
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  • 本篇論文提出手指靜脈之使用者辨識系統,開發在單晶片微處理器系統上。以CCD攝影機取得光穿透手指靜脈影像,經由C8051微處理器硬體實現影像切割處理與識別。本篇論文可分為兩個主要部分。第一部分為手指靜脈影像處理演算法的建構。第二部分為單晶片C8051手指靜脈血管影像處理的硬體實作方法,整個影像處理的步驟,包括二值化、中值濾波器、指靜脈影像使用者辨識等處理,這些方法都是使用Keil C程式語言所撰寫。我們初步的實驗結果可得知,此系統具可靠性與高準確率,且為低成本和高安全性的使用者辨識系統,未來將可應用於日常生活之中。


    This thesis aims at developing a microprocessor-based system to achieve a finger-vein user identification system. Light-transmitted finger images were acquired using a CCD camera, and the finger-vein images were subsequently segmented and recognized using hardware implemented on a C8051 microprocessor. The contributions of this thesis can be divided into two parts. The first part is the formation of image processing algorithm for finger-vein image segmentation. The second part is the hardware implementation of the proposed finger-vein image processing on a C8051 microprocessor. The whole processing steps, including binarization, median filter, and user recognition using images of finger vein, were performed on hardware written in Keil C computer language. Our preliminary results demonstrated the proposed system provides reliable and high-accuracy results, which can be used as a low-cost and high-security user identification system for daily-life applications in the future.

    摘要 I ABSTRACT II 致謝 III 目錄 IV 圖目錄 VI 表目錄 VIII 第一章 序論 1 1.1前言 1 1.2研究動機與目的 1 1.3文獻探討 2 1.4論文架構 3 第二章 研究背景 4 2.1手指靜脈血管識別簡介 4 2.2紅外光對於靜脈血管的特性 5 2.3手指靜脈血管影像擷取方式 7 2.4影像切割技術 9 第三章 研究方法與步驟 11 3.1系統架構 11 3.2軟體介紹 13 3.2.1 MATLAB程式語言 13 3.2.2 MCS-51程式語言與Keil C編譯器 15 3.3主控晶片介紹 16 3.4外接擴充記憶體模組 19 3.5手指靜脈血管影像處理演算法 21 3.5.1影像二值化 21 3.5.2中值濾波器 24 3.5.3去碎點 26 3.5.4比對 32 第四章 實驗結果 34 4.1實驗設計流程 34 4.2 樣本影像演算法模擬結果 35 4.2.1樣本影像1 35 4.2.2樣本影像2:模糊 38 4.2.3樣本影像3:更模糊 40 4.3手指靜脈血管影像處理演算法模擬之結果 42 4.3.1血管影像處理演算法模擬結果1 42 4.3.2血管影像處理演算法模擬結果2 44 4.3.3血管影像處理演算法模擬結果3 47 4.4以單晶片實現手指靜脈血管影像處理之結果 49 4.4.1以單晶片處理血管影像處理結果 49 4.4.2以單晶片處理血管影像辨識結果 53 第五章 結論與未來展望 56 5.1 結論 56 5.2未來展望 56 References 58 附錄A 61 A.1 系統實體圖 61

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