Basic Search / Detailed Display

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
高宗萬
Tzung-Wan Gau
顏成安
Cheng-An Yen
Degree: 碩士
Master
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
Reference times: Clicks: 462Downloads: 0
Share:
School Collection Retrieve National Library Collection Retrieve Error Report

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。
本論文將以低成本的硬體設備設計指靜脈辨識系統,期望在低品質的影像上也能有較高的辨識效果。不同於一般的指靜脈辨識,本論文採用反射法進行靜脈的擷取。首先決定擷取到影像的ROI,之後使用區域性灰階尺度正規化進行對比度的強化,再使用Sobel運算子對靜脈紋理強化,最後採用SURF進行特徵的擷取和比對。


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

[1] David Mulyono and Horng ShiJinn, "A study of finger vein biometric for personal identification," International Symposium on Biometrics and Security Technologies, 2008. ISBAST 2008, pp.1-8
[2] "生物辨識技術各分類研究與發展分析", http://www.digitimes.com.tw/tw/dt/n/shwnws.asp?cnlid=13&packageid=3324&id=0000173793_P278NER583OOLF4QEUQ10
[3] Mr. M.Mohamed syed Ibrahim, Dr. Faris Salman Ai-Namiy, Dr. Marsaline Beno and Dr. L.Rajaji. "Biometric Authentication for secured Transaction using Finger Vein Technology," Chennai and Dr.MGR University Second International Conference on Sustainable Energy and Intelligent System (SEISCON 2011)
[4] N. Miura, A. Nagasaka, and T. Miyatake, "Feature extraction of fingerveinpatterns based on repeated line tracking and its application topersonal identification," Mach. Vision Appl. 15(4), 194–203 (2004).
[5] N. Miura and A. Nagasaka, "Extraction of finger-vein patterns using-maximum curvature points in image profiles, " presented atMVA2005 IAPR Conf. on Machine Vision Applications, pp. 347–350,IEICE-INST Electronics Information Communications ENG, Tokyo(2005)
[6] Jinfeng Yang and Minfu Yan, "An Improved Method for Finger-vein Image Enhancement,” Signal Processing (ICSP), pp1706-1709, Oct 2010
[7] Wenming Yang, Qing Rao and Qingmin Liao, "Personal Identification For Single Sample Using Finger Vein Location and Direction Coding," Hand-Based Biometrics (ICHB), pp.1-6, Nov 2011
[8] 李雪妍, 郭樹旭, "融合指紋和指靜脈的多模態生物識別技術的研究," 吉林大學博士學位論文
[9] Junichi Hashimoto, "Finger Vein Authentication Technology and Its Future," Symposium on VLSI Circuits, 2006. Digest of Technical Papers. 2006, Honolulu, HI , PP. 5-8 (2006).
[10] " [創新趨勢] 一「手」就搞定:靜脈辨識技術", http://blog.uns.org.tw/node/209
[11] Herbert Bay, Tinne Tuytelaars, and Luc Van Gool, ETH Zurich, "SURF: Speeded Up Robust Features," Computer Vision and Image Understanding (CVIU), Vol. 110, No. 3, pp. 346–359, 2008
[12] 鐘國亮, "影像處理與電腦視覺," 東華書局, 2006
[13] Joung-Youn Kim, Lee-Sup Kim, and Seung-Ho Hwang. "An Advanced Contrast Enhancement Using Partially Overlapped Sub-Block Histogram Equalization," IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. 11, NO. 4, APRIL 2001.
[14] H. Bay, B. Fasel, and L. van Gool, "Interactive museum guide: Fast and robust recognition of museum objects," In Proceedings of the first international workshop on mobile vision, May 2006.
[15] H. Bay, T. Tuytelaars and L. Van Gool, "SURF: Speeded up robust features," In ECCV, 2006.
[16] Lowe, D. G., "Distinctive Image Features from Scale-Invariant Key-points," International Journal of Computer Vision, 60, 2, pp. 91-110, 2004.
[17] David G. Lowe, "Distinctive image features from scale-invariant key-points," International Journal of Computer Vision, 60, 2 (2004), pp. 91-110.
[18] 王永明, 王貴錦, "圖像局部不便性及描述," 國防工業出版社
[19] Viola P, Jones M, "Rapid object detection using a boosted cascade of simple features," In IEEE Conference on Computer Vision and Pattern Recognition, 2001
[20] Simard P, Bottou L, Haffner P,et al, "Boxlets: a fast convolution algorithm for signal processing and neural networks," Advances in Neural Information Processing Systems, 1999
[21] 曾若涵, "Feature extraction and matching of finger-vein patterns based on SURF(Speeded Up Robust Features), " 2011

無法下載圖示 Full text public date 2018/08/05 (Intranet public)
Full text public date This full text is not authorized to be published. (Internet public)
Full text public date This full text is not authorized to be published. (National library)
QR CODE