摘要翻译：
本文报告的跨传感器比较实验结果表明，我们的团队在2013年跨传感器比较竞赛中定义和模拟的将基于LG2200的生物识别系统迁移/升级到基于LG4000的生物识别系统的过程，在用户舒适度和系统安全性方面都比以前报告的LG4000-to-LG2200跨传感器虹膜识别结果更好。另一方面，我们定义和实现的LG2200-to-LG400迁移/升级过程适用于解决基于LG2200和基于LG4000的系统之间的互操作性问题，但也适用于在获取图像质量上具有相同变化的其他对系统。
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英文标题：
《Cross-Sensor Iris Recognition: LG4000-to-LG2200 Comparison》
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作者：
Nicolaie Popescu-Bodorin, Lucian Stefanita Grigore, Valentina Emilia
  Balas, Cristina Madalina Noaica, Ionut Axenie, Justinian Popa, Cristian
  Munteanu, Victor Stroescu, Ionut Manu, Alexandru Herea, Kartal Horasanli,
  Iulia Maria Motoc (ACSTL Cross-Sensor Comparison Competition Team 2013)
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最新提交年份：
2018
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分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Image and Video Processing        图像和视频处理
分类描述：Theory, algorithms, and architectures for the formation, capture, processing, communication, analysis, and display of images, video, and multidimensional signals in a wide variety of applications. Topics of interest include: mathematical, statistical, and perceptual image and video modeling and representation; linear and nonlinear filtering, de-blurring, enhancement, restoration, and reconstruction from degraded, low-resolution or tomographic data; lossless and lossy compression and coding; segmentation, alignment, and recognition; image rendering, visualization, and printing; computational imaging, including ultrasound, tomographic and magnetic resonance imaging; and image and video analysis, synthesis, storage, search and retrieval.
用于图像、视频和多维信号的形成、捕获、处理、通信、分析和显示的理论、算法和体系结构。感兴趣的主题包括：数学，统计，和感知图像和视频建模和表示；线性和非线性滤波、去模糊、增强、恢复和重建退化、低分辨率或层析数据；无损和有损压缩编码；分割、对齐和识别；图像渲染、可视化和打印；计算成像，包括超声、断层和磁共振成像；以及图像和视频的分析、合成、存储、搜索和检索。
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一级分类：Computer Science        计算机科学
二级分类：Computer Vision and Pattern Recognition        计算机视觉与模式识别
分类描述：Covers image processing, computer vision, pattern recognition, and scene understanding. Roughly includes material in ACM Subject Classes I.2.10, I.4, and I.5.
涵盖图像处理、计算机视觉、模式识别和场景理解。大致包括ACM课程I.2.10、I.4和I.5中的材料。
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英文摘要：
  Cross-sensor comparison experimental results reported here show that the procedure defined and simulated during the Cross-Sensor Comparison Competition 2013 by our team for migrating / upgrading LG2200 based to LG4000 based biometric systems leads to better LG4000-to-LG2200 cross-sensor iris recognition results than previously reported, both in terms of user comfort and in terms of system safety. On the other hand, LG2200-to-LG400 migration/upgrade procedure defined and implemented by us is applicable to solve interoperability issues between LG2200 based and LG4000 based systems, but also to other pairs of systems having the same shift in the quality of acquired images.
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PDF链接：
https://arxiv.org/pdf/1801.01695