Towards contactless palmprint recognition: A novel device, a new benchmark, and a collaborative representation based identification approach
Towards contactless palmprint recognition: A novel device, a new benchmark, and a collaborative representation based identification approach
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DOI：
10.1016/j.patcog.2017.04.016
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发表时间：
2017-09
期刊：
影响因子：
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通讯作者：
Lin Zhang;Lida Li;A. Yang;Ying Shen;Meng Yang
中科院分区：
文献类型：
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作者：
Lin Zhang;Lida Li;A. Yang;Ying Shen;Meng Yang
生物特征认证已被发现是一种有效的方法来识别一个人的身份，具有很高的可信度。在这一领域，掌纹的使用代表了最近的趋势。为了使基于掌纹的识别系统更加方便用户和卫生，研究人员一直在研究如何以非接触方式设计这种系统。尽管在这一领域已经投入了大量的努力，但由于缺乏使用精心设计的设备收集的公共的、大规模的和高质量的基准数据集，人们仍然不太清楚非接触式掌纹的鉴别能力。为了填补这一空白，我们首先开发了一种高度用户友好的设备，用于捕获高质量的非接触式掌纹图像。然后，利用所开发的设备，建立了一个大规模的掌纹图像数据集，包括在两个单独的会话中从600个不同的掌纹中收集的12,000张图像。据我们所知，这是迄今为止收集的最大的非接触式掌纹图像基准数据集。此外，首次采用现代图像质量评价指标对采集图像的质量进行了分析。此外，对于非接触式掌纹识别，我们提出了一种新颖的方法，即CR_CompCode，该方法可以在具有极低计算复杂度的情况下实现较高的识别精度。为了使结果完全可再现，收集的数据集和相关源代码可在http://sse.tongji.edu.cn/linzhang/contactlesspalm/index.htm上公开获得。
Biometric authentication has been found to be an effective method for recognizing a person’s identity with a high confidence. In this field, the use of palmprint represents a recent trend. To make the palmprint-based recognition systems more user-friendly and sanitary, researchers have been investigating how to design such systems in a contactless manner. Though substantial effort has been devoted to this area, it is still not quite clear about the discriminant power of the contactless palmprint, mainly owing to lack of a public, large-scale, and high-quality benchmark dataset collected using a well-designed device. As an attempt to fill this gap, we have at first developed a highly user-friendly device for capturing high-quality contactless palmprint images. Then, with the developed device, a large-scale palmprint image dataset is established, comprising 12,000 images collected from 600 different palms in two separate sessions. To the best of our knowledge, it is the largest contactless palmprint image benchmark dataset ever collected. Besides, for the first time, the quality of collected images is analyzed using modern image quality assessment metrics. Furthermore, for contactless palmprint identification, we have proposed a novel approach, namely CR_CompCode, which can achieve high recognition accuracy while having an extremely low computational complexity. To make the results fully reproducible, the collected dataset and the related source codes are publicly available at http://sse.tongji.edu.cn/linzhang/contactlesspalm/index.htm.