一個模組化指紋辨識驗證平台的研發

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：60

、訪客IP：3.133.152.153

姓名

黃艾聆(Ai-Ling Huang) 查詢紙本館藏

畢業系所

資訊工程學系在職專班

論文名稱

一個模組化指紋辨識驗證平台的研發
(Development of a Modular Fingerprint Recognition and Verification Platform)

相關論文

★ 整合GRAFCET虛擬機器的智慧型控制器開發平台	★ 分散式工業電子看板網路系統設計與實作
★ 設計與實作一個基於雙攝影機視覺系統的雙點觸控螢幕	★ 智慧型機器人的嵌入式計算平台
★ 一個即時移動物偵測與追蹤的嵌入式系統	★ 一個固態硬碟的多處理器架構與分散式控制演算法
★ 基於立體視覺手勢辨識的人機互動系統	★ 整合仿生智慧行為控制的機器人系統晶片設計
★ 嵌入式無線影像感測網路的設計與實作	★ 以雙核心處理器為基礎之車牌辨識系統
★ 基於立體視覺的連續三維手勢辨識	★ 微型、超低功耗無線感測網路控制器設計與硬體實作
★ 串流影像之即時人臉偵測、追蹤與辨識─嵌入式系統設計	★ 一個快速立體視覺系統的嵌入式硬體設計
★ 即時連續影像接合系統設計與實作	★ 基於雙核心平台的嵌入式步態辨識系統

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

至系統瀏覽論文 (2028-8-1以後開放)

摘要(中)

本研究旨在建立一個指紋辨識系統驗證平台，可分別針對指紋影像品質、指紋特徵點擷取正確性和指紋比對性能等功能模組進行獨立評估。此一驗證平台分為指紋資料庫管理、指紋影像品質評估、指紋特徵點擷取評估和指紋比對性能評估四個子系統。我們結合了網頁前後端技術，並使用Docker建立多個容器來實作這個平台軟體。最後採用多個實驗指紋資料庫來驗證這個平台的功能性。實驗結果表明，本研究能夠對指紋辨識三個功能模組進行個別評估，指紋影像品質模組能夠評估不同感測器或取像環境所獲得的影像品質指標；指紋特徵點擷取模組能夠計算指紋特徵點擷取的正確性，並可編輯和標註錯誤特徵；指紋比對模組產出代表辨識系統性能的相似度表和FAR、FRR不同閾值下的趨勢圖與ROC曲線。由於採用MIAT方法論設計，使得本平台的系統架構更加模組化；使用Docker容器讓本平台適用於跨平台的開發和佈署。

摘要(英)

This study aims to establish a verification platform for fingerprint recognition systems, which can independently evaluate modules such as fingerprint image quality, accuracy of fingerprint feature point extraction, and fingerprint matching performance. The verification platform consists of four subsystems: fingerprint database management, fingerprint image quality assessment, fingerprint feature point extraction evaluation, and fingerprint matching performance evaluation. We have combined web front-end and back-end technologies and utilized Docker to create multiple containers for implementing this platform software. Finally, multiple experimental fingerprint databases were used to verify the functionality of this platform. The experimental results demonstrate that our study enables the individual evaluation of the three functional modules of fingerprint recognition. The fingerprint image quality module can assess image quality indicators obtained from different sensors or imaging environments. The fingerprint feature point extraction module can calculate the accuracy of fingerprint feature point extraction and allows editing and labeling of erroneous features. The fingerprint matching module produces similarity tables, and trend charts representing the performance of the recognition system of FAR and FRR at different similarity threshold values, as well as ROC curves. By adopting the MIAT methodology, the system architecture of this platform becomes more modular, and the use of Docker containers enables cross-platform development and deployment of the platform.

關鍵字(中)

★ 指紋影像
★ 品質評估
★ 特徵擷取
★ 指紋辨識系統
★ 影像比對

關鍵字(英)

論文目次

摘要 i
ABSTRACT ii
誌謝 iii
目錄 iv
圖目錄 vi
表目錄 vii
第一章緒論 1
1.1 研究背景 1
1.2 研究目的 3
1.3 論文架構 3
第二章文獻回顧 4
2.1 指紋辨識流程 4
2.1.1 指紋影像預處理 5
2.1.2 特徵擷取 6
2.1.3 指紋比對 7
2.2 指紋影像品質 7
2.2.1 局部品質評估 8
2.2.2 全域品質評估 9
2.3 NFIQ 2評估標準 10
2.3.1 分割指紋影像 11
2.3.2 頻率域分析(FDA) 12
2.3.3 局部清晰度分數(LCS) 13
2.3.4 方向確定度水準(OCL) 14
2.3.5 方向流(OFL) 15
2.3.6 脊谷均勻度(RVU) 16
2.3.7 MU 16
2.3.8 MMB 17
2.3.9 Minutiae數量 17
2.3.10 Minutiae品質 17
2.3.11 ROI區域平均 18
2.3.12 ROI Orientation圖連續性總和 19
2.3.13 ROI相對orientation圖連續性總和 20
2.3.14 來自局部品質的品質向量 20
第三章系統設計 21
3.1 系統設計方法論 21
3.2 指紋資料庫模組設計 23
3.3 指紋評估模組設計 24
3.1.1 指紋影像品質評估模組 25
3.1.2 指紋特徵點擷取評估模組 26
3.1.3 指紋比對率評估模組 27
3.4 軟體整合實作 28
第四章驗證與實驗 30
4.1 實驗環境與資料庫 30
4.2 指紋影像品質評估實驗 32
4.3 指紋特徵點擷取實驗 37
4.4 指紋比對性能實驗 40
第五章結論與未來展望 49
5.1 結論 49
5.2 未來方向 50
參考文獻 51

參考文獻

[1] D. Maltoni., D. Maio, A. K. Jain. and J. Feng, "Handbook of Fingerprint Recognition. Third Edition," Springer Nature Switzerland, 2022.
[2] G. F. C. I. Watson, E. Tabassi, S. Cheng, P. Flanagan and W. Salamon, Fingerprint vendor technology evaluation, 2015.
[3] D. Maio, D. Maltoni, R. Cappelli, J. L. Wayman and A. K. Jain, "Fvc2002: Second fingerprint verification competition," Object recognition supported by user interaction for service robots, IEEE, vol. 3, pp. 811-814, 2002.
[4] D. Maio, D. Maltoni, R. Cappelli, J. L. Wayman and A. K. Jain, "Fvc2004: Third fingerprint verification competition," International conference on biometric authentication, pp. 1-7, 2004.
[5] R. Cappelli, M. Ferrara, A. Franco and D. Maltoni, "Fingerprint verification competition 2006," Biometric Technol. Today, vol. 15, pp. 7-9, 2007.
[6] M. M. Ali, V. H. Mahale, P. Yannawar and A. Gaikwad, "Overview of fingerprint recognition system," Proc. IEEE Int. Conf. Elect. Electron. Optim. Techn. (ICEEOT), pp. 1334-1338, 2016.
[7] N. B. Nill, "Test Procedures for Verifying Image Quality Requirements for Personal Identity Verification (PIV) Single Finger Capture Devices," MITRE MTR 060170, 2006.
[8] H. Kang, B. Lee, H. Kim, D. Shin and J. Kim, "A Study on Performance Evaluation of Fingerprint Sensors," Audio- and Video-Based Biometric Person Authentication. AVBPA 2003, pp. 574-583, 2003.
[9] R. Cappelli, M. Ferrara and D. Maltoni, "On the operational quality of fingerprint scanners," IEEE Transactions on Information Forensics and Security, vol. 3, no. 2, pp. 192-202, 2008.
[10] F. Alonso-Fernandez, J. Fierrez, D. Ramos and J. Ortega-Garcia, "Dealing with sensor interoperability in multi-biometrics: the UPM experience at the Biosecure Multimodal Evaluation 2007," SP IE Defense and Security Symposium, pp. 69440J-69440J, 2008.
[11] L. Ghiani, A. Hadid, G. L. Marcialis and a. F. Roli, "Fingerprint liveness detection using binarized statistical image features," Proc. IEEE 6th Int. Conf. Biometrics, Theory, Appl. Syst. (BTAS), pp. 1-6, 2013.
[12] J. J. Engelsma, S. S. Arora, A. K. Jain and N. G. Paulter, "Universal 3d wearable fingerprint targets: advancing fingerprint reader evaluations," IEEE Transactions on Information Forensics and Security, vol. 13, no. 6, pp. 1564-1578, 2018.
[13] T. Chugh, S. S. Arora, A. K. Jain and N. G. Paulter, "Benchmarking fingerprint minutiae extractors," 2017 International Conference of the Biometrics Special Interest Group (BIOSIG). IEEE, pp. 1-8, 2017.
[14] S. A. Grosz, J. J. Engelsma, N. G. P. Jr and A. K. Jain, "White-box evaluation of fingerprint matchers," arXiv preprint arXiv:1909.00799, 2019.
[15] S. A. Grosz, J. J. Engelsma, N. G. Paulter and A. K. Jain, "White-Box Evaluation of Fingerprint Matchers: Robustness to Minutiae Perturbations," 2020 IEEE International Joint Conference on Biometrics (IJCB), pp. 1-10, 2020.
[16] S. Grosz, J. Engelsma and A. Jain, "White-Box Evaluation of Fingerprint Recognition Systems," arXiv:2008.00128, 2020.
[17] F. Laricchia, "statista," 2022. [Online]. Available: https://www.statista.com/statistics/619788/average-smartphone-life/.
[18] "How people decide on a new smartphone: 91mobiles Smartphone Buyers Insights Survey 2022," team91, 2022. [Online]. Available: https://www.91mobiles.com/hub/how-people-decide-new-smartphone-buyers-survey-2022/.
[19] C. H. Chen, M. Y. Lin and X. C. Guo, "High-level Modeling and Synthesis of Smart Sensor Networks for Industrial Internet of Things," Computers & Electrical Engineering, vol. 61, pp. 48-66, 2017.
[20] C. H. Chen and C. T. Liu, "Person Re-Identification Microservice over Artificial Intelligence Internet of Things Edge Computing Gateway," Electronics 2021, vol. 10, no. 18, 2021.
[21] C. H. Chen, C. S. An and C. Y. Chen, "Fingerprint Quality Assessment Based on Texture and Geometric Features," Journal of Imaging Science and Technology, vol. 64, pp. 40403-1-40403-7, 2020.
[22] C. H. Chen, C. Y. Chen and T. M. Hsu, "Singular Points Detection in Fingerprints Based on Poincare Index and Local Binary Patterns," Journal of Imaging Science and Technology, vol. 63, no. 3, pp. 030401-1-7, 2019.
[23] A. Kumar and D. Zhang, "Combining fingerprint, palmprint and hand-shape for user authentication. In Pattern Recognition," ICPR. 18th International Conference on IEEE, vol. 4, pp. 549-552, 2006.
[24] R. Cappelli, D. Maio and D. Maltoni, "Semi-automatic enhancement of very low quality fingerprints," International Symposium on Image and Signal Processing and Analysis, p. 678–683, 2009.
[25] R. Abrishambaf, H. Demirel and I. Kale, "A fully CNN based fingerprint recognition system," Proc. 11th Int. Workshop Cell. Neural Netw. Appl, pp. 146-149, 2008.
[26] Z. H. Khazaal and S. S. Mahdi, "Fingerprint Identification based on Frequency Domain Analysis," 2019 4th Scientific International Conference Najaf (SICN), pp. 97-102, 2019.
[27] F. Zhao and X. Tang, "Preprocessing and postprocessing for skeleton-based ﬁngerprint minutiae extraction," Pattern Recognit, vol. 40, no. 4, p. 1270–1281, 2007.
[28] J. Zhang, R. Lai and C.-C. J. Kuo, "Latent fingerprint segmentation with adaptive total variation model," International Conference on Biometrics, pp. 189-195, 2012.
[29] J. Zhang, R. Lai and C.-C. J. Kuo, "Adaptive directional total variation model for latent fingerprint segmentation," IEEE Trans. on Information Forensics and Security, vol. 8, no. 8, p. 1261–1273, 2013.
[30] R. Kumar, P. Chandra and M. Hanmandlu, "Local directional pattern (LDP) based fingerprint matching using SLFNN," 2013 IEEE Second International Conference on Image Information Processing (ICIIP-2013), pp. 493-498, 2013.
[31] J. Svoboda, F. Monti and M. M. Bronstein, "Generative convolutional networks for latent fingerprint reconstruction," IEEE International Joint Conference on Biometrics, p. 429–436, 2017.
[32] J. F. J. Li and C.-C. J. Kuo, "Deep convolutional neural network for latent fingerprint enhancement," Signal Processing: Image Communication, vol. 60, pp. 52-63, 2018.
[33] P. Qian, A. Li and M. Liu, "Latent fingerprint enhancement based on DenseUNet," International Conference on Biometrics, pp. 1-6, 2019.
[34] M. Liu and P. Qian, "Automatic segmentation and enhancement of latent fingerprints using deep nested unets," IEEE Transactions on Information Forensics and Security, vol. 16, no. 1709–1719, 2020.
[35] Y. Zhu, X. Yin and J. Hu, "FingerGAN: A Constrained Fingerprint Generation Scheme for Latent Fingerprint Enhancement," IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 1-14, 2023.
[36] A. S. Deshpande, S. M. Patil and R. Lathi, "A Multimodel Biometric Recognition System based on Fusion of Palmprint Fingerprint and Face," Internntional Journal of Electronics and Computer Science Engineering, 2012.
[37] K.Zebbiche and F.Khelif, "Region-Based Watermarking of Biometrics Images: Case Study in Fingerprint Images," Proceedings of International Journal of Digital Multimedia Broadcasting, pp. 1-13, 2008.
[38] J. Yang, S. Xie, S. Yoon, D. Park, Z. Fang and S. Yang, "Fingerprint matching based on extreme learning machine," Neural Comput & Applic 22, p. 435–445, 2013.
[39] J. Zhou, F. Chen and J. Gu, "A novel algorithm for detecting singular points from fingerprint images," IEEE Trans. Pattern Anal. Mach. Intell, vol. 31, no. 7, pp. 1239-1250, 2009.
[40] K. Tiwari and P. Gupta, "Meandering energy potential to locate singular point of fingerprint," Proc. Int. Conf. Biometrics (ICB), pp. 1-6, 2016.
[41] A. I. Khan, "LAFIN: A convolutional neural network-based technique for singular point extraction and classification of latent fingerprints," Proc. Int. Conf. Soft-Comput. Netw. Secur. (ICSNS), pp. 1-7, 2018.
[42] L. Fan, S. Wang, H. Wang and T. Guo, "Singular points detection based on zero-pole model in fingerprint images," IEEE Trans. Pattern Anal. Mach. Intell, vol. 30, no. 6, pp. 929-940, 2008.
[43] Y. Wang, J. Hu and D. Phillips, "A fingerprint orientation model based on 2D Fourier expansion (FOMFE) and its application to singular-point detection and fingerprint indexing," IEEE Trans. Pattern Anal. Mach. Intell, vol. 29, no. 4, pp. 573-585, 2007.
[44] Y. Tang, F. Gao, J. Feng and Y. Liu, "FingerNet: An unified deep network for fingerprint minutiae extraction," Proc. IEEE Int. Joint Conf. Biometrics (IJCB), pp. 108-116, 2017.
[45] D. -L. Nguyen, K. Cao and A. K. Jain, "Robust Minutiae Extractor: Integrating Deep Networks and Fingerprint Domain Knowledge," 2018 International Conference on Biometrics (ICB), Gold Coast, QLD, Australia, pp. 9-16, 2018.
[46] J. J. Engelsma, K. Cao and A. K. Jain, "Learning a Fixed-Length Fingerprint Representation," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 43, no. 6, pp. 1981-1997, 2021.
[47] N. Sasuga, K. Ito and T. Aoki, "Fingerprint Feature Extraction Using CNN with Multiple Attention Mechanisms," 2022 IEEE International Joint Conference on Biometrics (IJCB), pp. 1-8, 2022.
[48] J. You, W. Kong, D. Zhang and K. Cheung, "On hierarchical palmprint coding with multiple features for personal identification in large databases," IEEE Trans. Circuits Syst. Video Technol, vol. 14, no. 2, pp. 234-243, 2004.
[49] R. Gayathri, "A Fingerprint and Palmprint Recognition Approach Based on Multiple Feature Extraction," European Journal of Scientific Research, vol. 76, pp. 514-526, 2012.
[50] Z. He, E. Liu and Z. Xiang, "Partial Fingerprint Verification via Spatial Transformer Networks," 2020 IEEE International Joint Conference on Biometrics (IJCB), pp. 1-10, 2020.
[51] S. Chen, Z. Guo, X. Li and D. Yang, "Query2Set: Single-to-Multiple Partial Fingerprint Recognition Based on Attention Mechanism," IEEE Transactions on Information Forensics and Security, vol. 17, pp. 1243-1253, 2022.
[52] K. Panetta, S. K. K. M, S. Rajeev and S. S. Agaian, "LQM: Localized Quality Measure for Fingerprint Image Enhancement," IEEE Access, vol. 7, pp. 104567-104576, 2019.
[53] M. F. Fahmy and M. A. Thabet, "A fingerprint segmentation technique based on morphological processing," Proc. IEEE Int. Symp. Signal Process. Inf. Technol. (ISSPIT), pp. 215-220, 2013.
[54] J. Liu, J. Yan, D. Deng and R. Zhang, "Fingerprint image quality assessment based on BP," IET Information Security, p. 185–195, 2020.
[55] E. Lim, X. Jiang and W. Yau, "Fingerprint quality and validity analysis," Proc. 2002 Int. Conf. on Image Processing, Rochester, vol. 1, pp. 1-1, 2002.
[56] E. Zhu, X. Guo and J. Yin, "Walking to singular points of fingerprints," Pattern Recognit, pp. 116-128, 2016.
[57] W. Jr and J. H, "Hierarchical grouping to optimize an objective function," J. Am. Stat. Assoc, p. 236– 244, 1963.
[58] T. Oblak, R. Haraksim, L. Beslay and P. Peer, "Fingermark Quality Assessment: An Open-Source Toolbox," 2021 International Conference of the Biometrics Special Interest Group (BIOSIG), pp. 1-7, 2021.
[59] "FingerJetFXOSE," DigitalPersona, 2011. [Online]. Available: https://github.com/FingerJetFXOSE/FingerJetFXOSE.
[60] E. Tabassi, M. Olsen, O. Bausinger, C. Busch, A. Figlarz, G. Fiumara, O. Henniger and J. Merkle, "NFIQ 2.0—NIST Fingerprint Image Quality," NIST-IR 8382, 2021.
[61] "VeriFinger," 1998. [Online]. Available: https://www.neurotechnology.com/verifinger.html.
[62] N. D. Kalka, M. Beachler and R. A. Hicklin, "Lqmetric: A latent fingerprint quality metric for predicting afis performance and assessing the value of latent fingerprints," Journal of Forensic Identification, vol. 70, pp. 443-463, 2020.
[63] E. Tabassi, C. Wilson and C. Watson, "Fingerprint Image Quality," NIST Research Report: NISTIR 7151, 2004.
[64] ISO/IEC. IS 29794-1:2016. information technology — biometric sample quality — part 1: Framework, ISO Standard, 2016.
[65] P. D. Kovesi, "MATLAB and Octave functions for computer vision and image processing," 2005. [Online]. Available: https://www.peterkovesi.com/matlabfns.
[66] T. Chen, X. Jiang and W. Yau, "Fingerprint image quality analysis," Image Processing, 2004. ICIP ’04. 2004 International Conference on, vol. 2, p. 1253–1256, 2004.
[67] N. Otsu, "A threshold selection method from gray-level histograms," Automatica, p. 23–27, 1975.
[68] S. Suzuki and K. be, "Topological structural analysis of digitized binary images by border following," Computer Vision,Graphics, and Image Processing, p. 32–46, 1985.
[69] M. Kass and A. Witkin, "Analyzing oriented patterns," Computer vision, graphics, and image processing, p. 362–385, 1987.
[70] "dorowu/ubuntu-desktop-lxde-vnc," Docker Inc., [Online]. Available: https://hub.docker.com/r/dorowu/ubuntu-desktop-lxde-vnc.

指導教授

陳慶瀚

審核日期

2023-7-17

推文