基于高斯多尺度聚集的生物识别手图像分割

A. Sierra, C. S. Ávila, J. Casanova, G. Bailador
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引用次数: 2

摘要

将生物识别技术应用到日常场景中,对软件和硬件都有很高的要求。相反,目前的生物识别技术也正在适应当今的设备,如移动电话、笔记本电脑等,这些设备远远不能满足先前规定的要求。事实上,实现这两种必需品的结合是目前生物识别技术中最困难的问题之一。因此,本文提出了一种能够在精度上为手部生物特征识别提供合适解决方案的分割算法,考虑到地毯、玻璃、草、泥、路面、塑料、瓷砖、木材等广泛的背景。结果表明,该算法的分割精度很高(F-measure≥88%),与最先进的分割算法相比,在时间上具有竞争力。
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Hand image segmentation by means of Gaussian multiscale aggregation for biometric applications
Applying biometrics to daily scenarios involves demanding requirements in terms of software and hardware. On the contrary, current biometric techniques are also being adapted to present-day devices, like mobile phones, laptops and the like, which are far from meeting the previous stated requirements. In fact, achieving a combination of both necessities is one of the most difficult problems at present in biometrics. Therefore, this paper presents a segmentation algorithm able to provide suitable solutions in terms of precision for hand biometric recognition, considering a wide range of backgrounds like carpets, glass, grass, mud, pavement, plastic, tiles or wood. Results highlight that segmentation accuracy is carried out with high rates of precision (F-measure ≥ 88%)), presenting competitive time results when compared to state-of-the-art segmentation algorithms time performance.
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