Bianconi F, Chirikhina E, Smeraldi F, Bontozoglou C, Xiao P
Department of Engineering, Università degli Studi di Perugia, 06125 Perugia, Italy.
School of Electrical Engineering and Computer Science, Queen Mary, University of London, London E1 4NS, UK.
Skin Res Technol. 2017 Aug;23(3):392-398. doi: 10.1111/srt.12348. Epub 2016 Nov 20.
BACKGROUND/PURPOSE: We investigate the use of skin texture features from the inner forearm as a means for personal identification. The forearm offers a number of potential advantages in that it is a fairly accessible area, and, compared with other zones such as fingertips, is less exposed to the elements and more shielded from wear.
We extract and combine skin textural features from two imaging devices (optical and capacitive) with the aim of discriminating between different individuals. Skin texture images from 43 subjects were acquired from three different body parts (back of the hand, forearm and palm); testing used the two sensors either separately or in combination.
Skin texture features from the forearm proved effective for discriminating between different individuals with overall recognition accuracy approaching 96%.
We found that skin texture features from the forearm are highly individual-specific and therefore suitable for personal identification. Interestingly, forearm skin texture features yielded significantly better accuracy compared to the skin of the back of the hand and of the palm of the same subjects.
背景/目的:我们研究将前臂内侧的皮肤纹理特征用作个人识别的一种手段。前臂具有许多潜在优势,因为它是一个相当容易触及的区域,并且与指尖等其他区域相比,较少暴露于外界因素且更不易磨损。
我们从两种成像设备(光学和电容式)中提取并组合皮肤纹理特征,目的是区分不同个体。从43名受试者的三个不同身体部位(手背、前臂和手掌)获取皮肤纹理图像;测试分别或组合使用这两种传感器。
前臂的皮肤纹理特征被证明对区分不同个体有效,总体识别准确率接近96%。
我们发现前臂的皮肤纹理特征具有高度个体特异性,因此适用于个人识别。有趣的是,与同一受试者的手背和手掌皮肤相比,前臂皮肤纹理特征产生的准确率明显更高。