School of Mathematics and Statistics, The University of New South Wales, Room RC-2050, Level 2, Red Center, East Wing, Sydney, NSW 2052, Australia.
IEEE Trans Pattern Anal Mach Intell. 2011 Jan;33(1):72-87. doi: 10.1109/TPAMI.2010.73.
Identifying incomplete or partial fingerprints from a large fingerprint database remains a difficult challenge today. Existing studies on partial fingerprints focus on one-to-one matching using local ridge details. In this paper, we investigate the problem of retrieving candidate lists for matching partial fingerprints by exploiting global topological features. Specifically, we propose an analytical approach for reconstructing the global topology representation from a partial fingerprint. First, we present an inverse orientation model for describing the reconstruction problem. Then, we provide a general expression for all valid solutions to the inverse model. This allows us to preserve data fidelity in the existing segments while exploring missing structures in the unknown parts. We have further developed algorithms for estimating the missing orientation structures based on some a priori knowledge of ridge topology features. Our statistical experiments show that our proposed model-based approach can effectively reduce the number of candidates for pair-wised fingerprint matching, and thus significantly improve the system retrieval performance for partial fingerprint identification.
从大型指纹数据库中识别不完整或部分指纹仍然是当今的一项艰巨挑战。现有的部分指纹研究侧重于使用局部脊线细节进行一对一匹配。在本文中，我们通过利用全局拓扑特征来研究通过检索候选列表来匹配部分指纹的问题。具体来说，我们提出了一种从部分指纹中重建全局拓扑表示的分析方法。首先，我们提出了一个用于描述重建问题的反向取向模型。然后，我们为反向模型的所有有效解提供了一个通用表达式。这允许我们在现有部分中保留数据保真度，同时探索未知部分中的缺失结构。我们还进一步开发了基于脊线拓扑特征的一些先验知识来估计缺失方向结构的算法。我们的统计实验表明，我们提出的基于模型的方法可以有效地减少指纹匹配的候选对数量，从而显著提高部分指纹识别的系统检索性能。
