Biometric identification system by lip shape
Biometric identification system by lip shape
复制标题
基于唇形的生物特征识别系统
DOI：
10.1109/ccst.2002.1049223
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发表时间：
2002
期刊：
影响因子：
--
通讯作者：
Miguel A. Ferrer
中科院分区：
文献类型：
--
作者：
E. Gómez;C. Travieso;Juan C. Briceño;Miguel A. Ferrer
基于唇形识别的生物特征识别系统引起了人们极大的兴趣，但在科学文献中却很少受到关注。这也许是因为人们认为它们几乎没有辨别力。然而，仔细的研究表明，嘴唇轮廓之间的差异大于同一人在不同嘴唇图像上的形状之间的差异。因此，通过嘴唇轮廓进行生物特征识别是可能的。本文从彩色人脸图像中提取嘴唇轮廓：利用Chang等（1994）的变换将彩色图像转换为灰度，并采用Ridler和Calvar阈值进行二值化。将嘴唇质心考虑为坐标的原点，每个像素嘴唇包络用极坐标（从-/spl pi/到+/spl pi/排序）和笛卡尔坐标（按高度和宽度排序）参数化。为了评估身份，多标记的多参数隐马尔可夫模型与极坐标和多层神经网络应用于笛卡尔坐标。在50人的数据库中，平均分类命中率为96.9%，等误率（EER）为0.015。
Biometrics systems based on lip shape recognition are of great interest, but have received little attention in the scientific literature. This is perhaps due to the belief that they have little discriminative power. However, a careful study shows that the difference between lip outlines is greater than that between shapes at different lip images of the same person. So, biometric identification by lip outline is possible. In this paper the lip outline is obtained from a color face picture: the color image is transformed to the gray scale using the transformation of Chang et al. (1994) and binarized with the Ridler and Calvar threshold. Considering the lip centroid as the origin of coordinates, each pixel lip envelope is parameterized with polar (ordered from -/spl pi/ to +/spl pi/) and Cartesian coordinates (ordered as heights and widths). To asses identity, a multilabeled multiparameter hidden Markov model is used with the polar coordinates and a multilayer neural network is applied to Cartesian coordinates. With a database of 50 people an average classification hit ratio of 96.9% and equal error ratio (EER) of 0.015 are obtained.