研究生: |
江振宇 CHEN-YU CHIANG |
---|---|
論文名稱: |
加速強健特徵點及CCH來設計一個有效的掌靜脈裝置 Using SURF and CCH to design an effective Palm Vein Recognition device |
指導教授: |
洪西進
Shi-Jinn Horng |
口試委員: |
鍾國亮
Kuo-Liang Chung 王有禮 Yue-Li Wang |
學位類別: |
碩士 Master |
系所名稱: |
電資學院 - 資訊工程系 Department of Computer Science and Information Engineering |
論文出版年: | 2012 |
畢業學年度: | 100 |
語文別: | 中文 |
論文頁數: | 49 |
中文關鍵詞: | 生物辨識 、掌靜脈 、賈伯濾波器 、CCH(Contrast Context Histogram) 、加速強健特徵點 |
外文關鍵詞: | biometric recognition, palm vein, Gabor filter, CCH(contrast context histogram), SURF |
相關次數: | 點閱:308 下載:2 |
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在生物識別領域中,人類的靜脈特徵屬於新的生物辨識研究課題,為求使用方便,目前常見的靜脈辨識技術大致為手指靜脈、手掌靜脈等。靜脈辨識屬於活體辨識,由於靜脈的資訊都位於皮膚內層,有著不易仿造之優勢,為目前生物辨識較新的議題。目前許多相關研究,為求取得的靜脈影像清晰,使用的機構多數為高畫質的紅外線CCD攝影機。在本研究中,我們嘗詴採用市面上CMOS的紅外線camera為本實驗的機構。由於手掌蘊含豐富的靜脈特徵,我們以手掌靜脈辨識系統做為本次實驗的主題。 本論文提出兩種手掌靜脈特徵擷取方式,分別為Harris角點和SURF特徵極值。首先,將harris角點以CCH(Contrast context histogram,CCH)建立起角點特徵向量,利用角點特徵做初步特徵比對,篩選出第一階段的候選集。針對此候選集取出SURF特徵極值,並且以SURF特徵做第二階段比對,找出最相似者是否為受測者本人,此方式有助於整體辨識率的提升。
The biometric is very popular in recent years. The common biometrics features such as palmprint, fingerprint, iris, face. In daily life, many applications have developed based on the biometrics. In biometrics field, the vein recognitions are a novel research. Most of the vein recognitions are finger vein, palm vein and so on. The Vein information is effective only in vivo and difficult to forge because of inside the superficial skin. In order to capture clear images, many related studies which based on CCD high resolution near infrared camera. In this research, we attempted to use CMOS camera as our captured equipment. There are rich of information in Palm vein image for authentication, and it provides high accurate recognition rate. In this paper, we proposed two methods of features extraction, one is Harris corner detection and the other is SURF(Speeded up robust feature). First, we constructed feature descriptors in corner points with CCH(Contrast context histogram), and find candidate sets by comparing those feature descriptors. In those candidate sets, we extract feature points again with SURF, and they can be used to double authentication and achieve higher accuracy authentication.
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