Subject Review: Hand Vascular Pattern Technology

Shaimaa Khudhair Salah, A. O. Khalaf
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引用次数: 0

Abstract

Vein recognition systems are a form of biometric recognition that can distinguish people according to their vascular structure. Identification from hand-wrist vein pattern is one of these systems. In this study, hand-wrist vein images taken from people using an infrared light source with a wavelength of 850 nm were segmented by passing through various image processing algorithms. Scale-independent feature transformation (SURF) method was used for key point extraction from segmented images. The features obtained by the SURF method are rotation, camera angle, ambient light intensity, etc. This method has been preferred because it is invariant against situations. In the identification process, the Euclidean distance method was used by making use of the extracted key points. The accuracy rate was determined as 97% as a result of the matching processes using the hand-wrist vein patterns in the database.
主题综述:手部血管模式技术
静脉识别系统是一种生物识别的形式,可以根据人的血管结构来区分人。手-腕部静脉形态识别就是其中一个系统。在本研究中,使用波长为850 nm的红外光源,通过各种图像处理算法对人的手腕静脉图像进行分割。采用尺度无关特征变换(SURF)方法对分割后的图像进行关键点提取。SURF方法获得的特征包括旋转、相机角度、环境光强度等。这种方法是首选的,因为它对各种情况都是不变的。在识别过程中,利用提取的关键点进行欧几里得距离法。通过使用数据库中的手腕静脉模式进行匹配处理,确定准确率为97%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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