研究生: |
鄭又誠 Yo-chen Cheng |
---|---|
論文名稱: |
基於Gabor-Min紋理重建強化實現雙重掌靜脈特徵之辨識裝置 Apply Bi-Features to Implement a Palm Vein Recognition System and Device Based on Gabor-Min |
指導教授: |
洪西進
Shi-Jinn Horng |
口試委員: |
林韋宏
Wei-hong Lin 高宗萬 Tzung-Wan Gau 顏成安 Cheng-An Yen |
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: | 2013 |
畢業學年度: | 101 |
語文別: | 中文 |
論文頁數: | 63 |
中文關鍵詞: | 生物特徵 、手掌靜脈 、特徵擷取 、紋理重建強化 |
外文關鍵詞: | Biometrics, Palm vein, Features extraction, texture reconstruction |
相關次數: | 點閱:603 下載:0 |
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生物特徵辨識是近年來相當受重視的研究課題,主要是利用人體生理或行為特徵進行身分識別。本研究所採用的手掌靜脈資訊,便屬生物特徵辨識的一種實現。人體的靜脈資訊於成年後其結構上大致呈現穩定的分佈,並具備單一存在的特性。又因資訊位於皮膚內層且屬於活體辨識,隱匿性高不易仿造,因此在眾多生物特徵中,被視為極具潛力與優勢的選擇。
本研究設計了一套全新的手掌靜脈資訊擷取裝置,該裝置能確實地固定手掌位置與手掌肌肉伸展的程度,為辨識上提供良好的偵測環境基礎。在靜脈辨識系統上,提出了兩階段的雙重特徵辨識:(1)Harris角點的CCH特徵;(2)Gabor-Min紋理重建強化後之SURF特徵。系統同時建立歷史記錄更新的機制,有助於整體辨識率的提升與確保長期使用下的穩定性。經實驗數據證實,與先前論文比較,本論文的硬體機構設計與提出的辨識方法擁有較高的辨識率及低成本的優勢。
One of the most enlightened subjects in science field these years is Biometric – which recognizes one’s identity through either his physiological or behavioral characteristics. And our research in adopting the information of palm vein is the realization of Biometric. One person’s vein information mostly remains stable in its pattern as growing older, and carries its unity. Also, because this information is ingrained deeply in a skin, the information for Vivo Identification, it could not be possibly duplicated thanks to its high occultation. Therefore, Palm Vein Feature is regarded as the most potential and advantageous option out of many Bio-Characteristics.
In this study, we come out of a whole new design which is able to firmly fix one’s palm position and the degree of (palm) muscle stretch, providing a better detecting environment of identification. Also, in the palm vein identification system, we put forward the two-phased multiple feature identification – Harris corner vector of CCH (Contrast Context Histogram), and the SURF (Speeded Up Robust Features) vector based on Gabor-Min texture reconstruction. This system also creates a mechanism of updating historical records, which helps increasing the accuracy of identification and the stability under long-time use. Proved by experimental results, and to compare with former thesis, this thesis including hardware design and the proposition of identifying method in it, truly has advantages of higher recognizing ratios and lower costs.
[1] Senao International CO., LTD, “生物辨識(Biometric)系統,” http://www.senao.com.tw/proLife_Content.aspx?id=437.
[2] 國家政策網路智庫, “運用生物特徵辨識身分制度之比較研究,” http://thinktank.nat.gov.tw/lp.asp?ctNode=146&CtUnit=7&BaseDSD=11&mp=1&htx_ghtx.topcat=18982.
[3] Annual Biometric Industry Revenues, http://www.biometricgroup.com.
[4] Masaki Watanabe, Toshio Endoh, Morito Shiohara and Shigeru Sasaki, “Palm Vein Authentication Technology and Its Applications, “ The Biometric Consortium Conference, pp. 1-2, September 19-21, 2005, USA.
[5] Naoto Miura, Akio Nagasaka and Takafumi Miyatak, ”Feature Extraction of Finger-vein Patterns Based on Repeated Line Tracking and Its Application to Personal Identification,” Machine Vision and Applications, pp. 194–20, 21 July 2004.
[6] Wang Lingyu and Graham Leedham, ”Near- and Far- Infrared Imaging for Vein Pattern Biometrics,“ IEEE International Conference on Video and Signal Based Surveillance, pp. 52-57, Nov 2006.
[7] Sanchit, Mauricio Ramalho , Paulo Lobato Correia and Luis Ducla Soares, “Biometric Identification through Palm and Dorsal Hand Vein Patterns,” EUROCON - International Conference on Computer as a Tool (EUROCON), pp. 1-4 , 27-29 April 2011.
[8] Huan Zhang and Dewen Hu, "A Palm Vein Recognition System," International Conference on Intelligent Computation Technology and Automation, 2010.
[9] Jian-Gang Wang, Wei-Yun Yau and Andy Suwandy, "Feature-level Fusion of Palmprint and Palm Vein for Person Identification Based on A “Junction Point”,” Institute for Infocomm Research, A*STAR (Agency for Science, Technology and Research), Fusionopolis, Singapore, ICIP, 2008.
[10] Hao Li, Zhenhua Guo, Shouyu Ma and Nan Luo, "A New Touchless PalmPrint Location Method Based on Contour Centroid," Hand-Based Biometrics (ICHB), IEEE, 2011.
[11] Goh Kah Ong Michael, Tee Connie and Andrew Beng Jin Teoh, "Touch-less Palm Print Biometrics: Novel Design and Implementation," Image and Vision Computing 26 (2008).
[12] Leila Mirmohamadsadeghi and Andrzej Drygajlo, "Palm Vein Recognition with Local Binary Patterns and Local Derivative Patterns," Proceedings of the International Joint Conference on Biometrics,Pages 1-6, 2011.
[13] Goh Kah Ong Michael, Tee Connie and Andrew Teoh Beng Jin, "Design and Implementation of a Contactless Palm Print and Palm Vein Sensor,"11th International Conference Control, Automation, Robotics and Vision, Jin.2010.
[14] Goh Kah Ong Michael, Tee Connie and Andrew Teoh Beng Jin, "A Preliminary Acclimatization Study of a Contactless Biometrics using Palm Vein Feature" Industrial Electronics and Applications (ICIEA), 2011 6th IEEE Conference.
[15] Rajendran Jeyaprakash, Jin Lee, Subir Biswas and Jae Mook Kim, ” Secured Smart Card using Palm Vein Biometric On-Card-Process,” International Conference on Convergence and Hybrid Information Technology, pp. 548 – 551, 28-30 Aug. 2008.
[16] B.Prasanalakshmi and A.Kannammal, “Secure Cryptosystem from Palm Vein Biometrics in Smart Card, ” Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on, pp. 653 – 657, 26-28 Feb. 2010.
[17] Jing-Wein Wang and Tzu-Hsiung Chen, "Building Palm Vein Capturing System for Extraction," 21st International Conference on Systems Engineering, 2011.
[18] Ajay Kumar and K. Venkata Prathyusha, “Personal Authentication Using Hand Vein Triangulation and Knuckle Shape,” IEEE Transactions On Image Processing, pp. 2127 – 2136, Sept. 2009.
[19] C. Harris and M.J. Stephens, “A Combined Corner and Edge Detector, “ In Alvey Vision Conference, pp. 147–152, 1988.
[20] Chun-Rong Huang, Chu-Song Chen and Pau-Choo Chung, “Contrast Context Histogram - An Efficient Discriminating Local Descriptor for Object Recognition and Image Matching,“ 18th International Conference on Pattern Recognition, ICPR, pp. 53-56, 2006.
[21] Herbert Bay , Andreas Ess , Tinne Tuytelaars and Luc Van Gool, “Speeded-Up Robust Features (SURF),“ Computer Vision and Image Understanding 110, pp. 346–359, 2008.
[22] J.G. Daugman, “Two-Dimensional Spectral Analysis of Cortical Receptive Field Profiles,” Vision Research, vol. 20, pp. 847-856, 1980.
[23] L. Marinez-Fonte, S. Gautama, and W. Philips, "An Empirical Study of Corner Detection to Extract Buildings in Very High Resolution Satellite Images," Proceedings of ProRISC, pp.288-293.
[24] 莊仁輝,「家用機器人之電腦視覺系統研發」,行政院國家科學委員會專題研究計劃期中進度報告,2002。
[25] DAVID G. LOWE, “Distinctive Image Features from Scale-Invariant Keypoints,“ International Journal of Computer Visio, 2004.
[26] Stephen Se, David Lowe and Jim Little, “Vision-based Mobile Robot Localization and Mapping Using Scale-Invariant Features,” Int. Conf. on Robotics and Automation(ICRA), 2001.
[27] Stephen Se, Ho-Kong Ng, Piotr Jasiobedzki and Tai-Jing Moyung, “Vision Based Modeling and Localization for Planetary Exploration Rovers,” 55th Int. Astronautical Congress, Canada, 2004.
[28] Herbert Bay, Tinne Tuytelaars, Luc Van Gool and ETH Zurich, “ SURF: Speeded Up Robust Features,” Computer Vision and Image Understanding (CVIU), Vol. 110, No. 3, pp. 346–359, 2008.
[29] 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.
[30] H. Bay, T. Tuytelaars and L. Van Gool, “SURF: Speeded up Robust Features,” In ECCV, 2006.
[31] Simard P, Bottou L and Haffner P, "Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks," Advances in Neural Information Processing Systems, 1999.
[32] Viola P, Jones M, "Rapid Object Detection using A Boosted Cascade of Simple Features," In IEEE Conference on Computer Vision and Pattern Recognition, 2001.
[33] Johannes Bauer, Niko Sunderhauf and Peter Protzel, “Comparing Several Implementations of Two Recently Published Feature Detectors,” In Proc. of the International Conference on Intelligent and Autonomous Systems, IAV, Toulouse, France, 2007.
[34] Yuhang Ding, Dayan Zhuang and Kejun Wang “A Study of Hand vein Recognition Method”, Proceedings of the IEEE International Conference on Mechatronics & Automation Niagara Falls, Canada, July 2005.
[35] Ajay Kumar and K. Venkata Prathyusha, “Personal Authentication Using Hand Vein Triangulation and Knuckle Shape, ” IEEE Transactions on Image Processing,” pp. 2127 – 2136 , Sept. 2009.
[36] Yi-Bo Zhang, “Palm Vein Extraction and Matching for Personal
Authentication,“ VISUAL 2007, LNCS 4781, pp. 154-164, 2007.
[37] Jing-Wein Wang , “Building Palm Vein Capturing System for Extraction,“ Systems Engineering (ICSEng), 2011, 21st International Conference, pp. 311-314, 16-18 Aug. 2011.
[38] Khan, M.H.-M. , “Dorsal Hand Vein Biometric using Independent Component Analysis (ICA),“ Internet Technology and Secured Transactions (ICITST) , pp. 191 - 195 , 11-14 Dec. 2011.
[39] 牟宗懷, “Using 2D Gabor Filters and SIFT Features to design an effective Palm vein and Palmprint Recognition device,” 2010.
[40] 江振宇, “Using SURF and CCH to Design an Effective Palm Vein Recognition Device,” 2012.