| 摘要: | 摘要： For many practical applications of image sensors, how to extend the depth-of-field (DoF) is an important research topic; if successfully implemented, it could be beneficial in various applications, from photography to biometrics. In this work, we want to examine the feasibility and practicability of a well-known “extended DoF” (EDoF) technique, or “wavefront coding,” by building real-time long-range iris recognition and performing large-scale iris recognition. The key to the success of long-range iris recognition includes long DoF and image quality invariance toward various object distance, which is strict and harsh enough to test the practicality and feasibility of EDoF-empowered image sensors. Besides image sensor modification, we also explored the possibility of varying enrollment/testing pairs. With 512 iris images from 32 Asian people as the database, 400-mm focal length and F/6.3 optics over 3 m working distance, our results prove that a sophisticated coding design scheme plus homogeneous enrollment/testing setups can effectively overcome the blurring caused by phase modulation and omit Wiener-based restoration. In our experiments, which are based on 3328 iris images in total, the EDoF factor can achieve a result 3.71 times better than the original system without a loss of recognition accuracy.
其他題名： Sensors (Basel)
出版者： Switzerland: MDPI AG
出版日期： 2016-11-25
出處： Sensors (Basel, Switzerland), 2016-11, Vol.16 (12), p.1994-1994
資源來源： Publicly Available Content Database
版權： Copyright MDPI AG 2016
版權： 2016 by the authors; licensee MDPI, Basel, Switzerland. 2016
識別號： ISSN: 1424-8220
識別號： EISSN: 1424-8220
識別號： DOI: 10.3390/s16121994
識別號： PMID: 27897976 |
