【16-02期VALSE Webinar活动】  报告嘉宾2：冯建江（清华大学）
报告时间： 2016年1月13日（星期三）晚21:00（北京时间）
报告题目：Statistical Model Based Detection, Segmentation, and Enhancement with Applications in Fingerprint Recognition [Slides]
主持人： 韩琥（中科院计算所）
报告摘要：
Latent fingerprints have been used by law enforcement agencies to identify suspects for a century. However, because of poor image quality and complex background noise, latent fingerprints are routinely identified relying on features manually marked by human experts in practice. A large number of latent fingerprints cannot be treated in time due to lacking well trained experts, highlighting the need for fully automatic systems. We propose a systematic algorithm for latent fingerprint detection, segmentation, and orientation field estimation, without any manual markup. The proposed algorithm is based on a statistical model of fingerprint orientation fields, localized orientation dictionaries. Multiple potential latent fingerprints are detected using a sequential pose estimation algorithm. Then, the full orientation field and confidence map of each detected fingerprint are estimated based on localized dictionaries lookup. Finally, the boundary of each latent fingerprint is delineated by analyzing its confidence map. Experiments on a multi-latent fingerprint database and the challenging NIST SD27 latent fingerprint database show the effectiveness of the proposed algorithm.
参考文献：
[1] Xuanbin Si, Jianjiang Feng, Jie Zhou, Yuxuan Luo: Detection and Rectification of Distorted Fingerprints. IEEE Trans. Pattern Anal. Mach. Intell. 37(3): 555-568 (2015).
[2] Xiao Yang, Jianjiang Feng, Jie Zhou: Localized Dictionaries Based Orientation Field Estimation for Latent Fingerprints. IEEE Trans. Pattern Anal. Mach. Intell. 36(5): 955-969 (2014).
[3] Jianjiang Feng, Jie Zhou, Anil K. Jain: Orientation Field Estimation for Latent Fingerprint Enhancement. IEEE Trans. Pattern Anal. Mach. Intell. 35(4): 925-940 (2013).
[4] Jianjiang Feng, Anil K. Jain: Fingerprint Reconstruction: From Minutiae to Phase. IEEE Trans. Pattern Anal. Mach. Intell. 33(2): 209-223 (2011).
[5] Xuanbin Si, Jianjiang Feng, Jie Zhou: Enhancing latent fingerprints on banknotes. IJCB 2014: 1-8.
报告人简介：
Jianjiang Feng is an associate professor in the Department of Automation at Tsinghua University, Beijing. He received the BS and PhD degrees from the School of Telecommunication Engineering, Beijing University of Posts and Telecommunications, China, in 2000 and 2007, respectively. From 2008 to 2009, Dr. Feng was a postdoctoral researcher in the PRIP Lab at Michigan State University. Dr. Feng’s research interests include fingerprint recognition and computer vision, and he has 16 years research experience in fingerprint recognition, and is the PI of two NSFC award. His fingerprint recognition technologies have been licensed to top biometrics companies from all over the world. Dr. Feng has published over than 40 peer-reviewed academic papers on top journals and conferences, including 9 regular papers on IEEE T-PAMI, and applied 20+ patents in China and 4 patents in US. Dr. Feng received three best paper awards from the Int’l Conference on Biometrics (ICB), two second-place awards of natural science from the Chinese Ministry of Education, and the first-place award of Advance of Science and Technology from the Chinese Institute of Electronics. Dr. Feng is an associate editor of Image and Vision Computing, and area chair of ICB.
冯建江，清华大学自动化系副教授，主要研究方向为图像处理与模式识别。分别于2000年和2007年在北京邮电大学获得本科与博士学位，2008-2009年在美国密歇根州立大学Anil K. Jain研究组担任博士后研究员，从事指纹识别研究工作。在指纹识别领域有16年研究经历，承担国家自然科学基金项目2项；在计算机视觉与生物特征识别领域发表学术论文40多篇，其中IEEE T-PAMI长文9篇；先后申请国内发明专利20余项、美国发明专利4项。所研发的整形指纹检测技术、低质量指纹增强技术授权国内外顶尖企业。先后获International Conference on Biometrics（ICB）等会议最佳论文奖3次、教育部自然科学类二等奖2次以及电子学会科技进步类一等奖。目前担任《Image and Vision Computing》编委（2014年至今）、ICB领域主席（2014年至今）。 | 
