Tongue Verification with Manifold Learning

摘要：

As an important human organ, tongue carries abundant individual features and has been considered as a novel biometrics. However, hitherto little work has been done it. The main reason is that it is difficult to capture the features of human tongue. This paper presents a novel framework for modeling and recognizing human tongue based on image sequences. This method exploits manifold learning dimensionality reduction, leading to a low-dimensional embedding of tongue image sequence for verification. To match the embedded manifolds, the Hausdorff distance is used for similarity measures. Classification is then achieved in a nearest neighbor framework. Based on the tongue images database, the promising experimental results demonstrate that not only the validity of tongue biometric but also the effectiveness and robustness of the proposed method.

关键词： Biometrics human tongue manifold learning dimensionality reduction locality preserving projections

作者: Zhi Liu Hongjun Wang Wei Jiang Huawei Zhuang

作者单位: School of Information Science and Engineering Shandong University Jinan, China Institute of Information and Electrical Engineering Shandong Jianzhu University Jinan, China

会议类型: 国际会议

会议名称: 2011 Seventh International Conference on Natural Computation(第七届自然计算国际会议 ICNC 2011)

会议地点: 上海

会议语种:英文

页码: 2395-2398

在线出版日期: 2011-07-26（万方平台首次上网日期，不代表论文的发表时间）