Multi-finger knuckle recognition from video sequence: Extracting accurate multiple finger knuckle regions
Multi-finger knuckle recognition from video sequence: Extracting accurate multiple finger knuckle regions
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DOI：
10.1109/btas.2014.6996236
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发表时间：
2014-12
期刊：
影响因子：
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通讯作者：
Daichi Kusanagi;Shoichiro Aoyama;Koichi Ito;T. Aoki
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文献类型：
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作者：
Daichi Kusanagi;Shoichiro Aoyama;Koichi Ito;T. Aoki
提出了一种多指关节识别系统，并提出了一种基于视频序列的指关节区域提取算法。由于可以从一组图像帧中选择最佳图像帧来提取每个手指要匹配的区域，因此使用视频序列可以实现稳定和鲁棒的手指关节区域提取。通过一组实验，我们证明了该算法对食指、中指、无名指和小指的提取率分别为96.4%、99.4%、97.6%和96.4%，在实践中可以接受。结果表明，在大多数情况下，四指身份验证是可行的。我们还证明了使用多个手指关节区域对人员身份验证具有有效的性能。
This paper presents a multi-finger knuckle recognition system and proposes a finger knuckle region extraction algorithm from a video sequence. The use of video sequences makes it possible to achieve stable and robust finger knuckle region extraction, since the optimal image frame can be selected from a set of image frames to extract a region to be matched for each finger. Through a set of experiments, we demonstrate that the extraction rates of the proposed algorithm are 96.4%, 99.4%, 97.6% and 96.4% for index, middle, ring and little fingers, respectively, which are acceptable in practice. The result indicates that four fingers can be used for person authentication in most cases. We also demonstrate that the use of multiple finger knuckle regions exhibits efficient performance for person authentication.