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Fingerprint recognition technology plays a critical role in modern security and information protection. Traditional 2D fingerprint recognition methods are still limited due to an imbalance between growing security demands and inefficiency of encoding detailed information. Although various 3D fingerprint technologies have been introduced recently, their practical applications are restricted by complex sampling procedures and bulky equipment. This paper proposes a new 3D fingerprint fragments reconstruction method based on the condensation of microdroplet clusters, resulting in efficiently extracting detailed structural information from fingerprint patterns. By identifying the unique topological features of fingerprint valleys, a micrometer-scale vapor transport model is developed. A differential approach is used to divide the microdroplet clusters formed when a finger is pressed on a cold surface into discrete units. In each unit, the diffusion distance and mass transfer in the condensation process are calculated. Nonlinear regression techniques are then utilized to reconstruct the 3D fingerprint fragments. Furthermore, the experimental validation shows excellent consistency with premeasured fingerprint data, with a reconstruction error of less than 9.3%. It has made a significant improvement in capturing high-density fingerprint data in a short period of time, completing the data acquisition in less than 1 second. Compared with ultrasound imaging techniques, this method significantly shortens the acquisition time, which typically involve complex procedures. Additionally, it offers a more efficient alternative to deep learning methods, which require extensive data training and computational processes. This 3D fingerprint reconstruction method provides an efficient, low-cost and easy-to-operate solution. It holds the potential to significantly enhance personal identification and information protection systems, contributing to the advancement of 3D fingerprint recognition technology in practical applications.
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图 1 基于冷凝液滴特征分析的3D指纹重构流程图
Figure 1. 3D Fingerprint reconstruction process based on condensed droplet characteristics.
图 2 冷凝液滴图像采集 (a) 冷凝液滴发生图像采集装置; (b) 冷凝液滴带分布图; (c) 指纹结构显微图
Figure 2. Condensate droplet image capture: (a) Image acquisition setup for condensed drop; (b) distribution of condensation droplet bands; (c) microscopic image of fingerprint structure.
图 3 不同基底表面特性对液滴行为的影响比较 (a) 普通硅片与疏水硅片的接触角测量; (b) 普通硅片与疏水硅片上液滴冷凝效果对比
Figure 3. Comparison of the effect of Substrate surface properties on droplet behavior: (a) Contact angle measurements on standard and hydrophobic silicon wafers; (b) droplet condensation performance on standard and hydrophobic silicon wafers.
图 4 毛细管模拟实验图 (a) 模具结构正视图; (b) 模具结构俯视图; (c) 模具按压冷表面所得冷凝液滴分布图
Figure 4. Capillary simulation experiment: (a) Front view of the mold structure; (b) top view of the mold structure; (c) distribution of condensate drops on the cold surface pressed by the mold.
图 5 指纹犁沟模型建立及其有效性分析 (a) 犁沟内水蒸气输运微观示意图; (b) 冷凝液滴传质面积计算示意图; (c) 指纹片段冷凝微滴群图像; (d) 指纹片段水蒸气传质距离图; (e) 指纹片段重构结果3D图
Figure 5. Establishment of the fingerprint valley model and effectiveness analysis: (a) Schematics of the microscopic vapor transfer within the valley; (b) schematic of mass transfer area calculation for condensed drops; (c) image of condensed droplet clusters on the fingerprint segment; (d) vapor mass transfer distance within the fingerprint segment; (e) 3D reconstruction of the fingerprint segment.
图 6 三维指纹重构 (a) 指纹样品激光扫描图; (b) 扫描所得指纹片段三维形貌; (c) 指纹片段对应冷凝液滴带分布图; (d) 重构所得指纹片段三维形貌
Figure 6. 3D reconstruction of fingerprints: (a) Laser scan of the fingerprint sample; (b) 3D morphology of the fingerprint segment derived from the scan; (c) distribution of condensation droplet bands corresponding to the fingerprint segment; (d) 3D morphology of the reconstructed fingerprint segment.
图 7 2D轮廓图 (a) 原始指纹片段轮廓图; (b) 重构指纹片段轮廓图
Figure 7. 2D contour map: (a) Original fingerprint fragment contour map; (b) reconstructed fingerprint fragment contour map.
图 8 三维指纹重构误差分析热图
Figure 8. 3D Fingerprint reconstruction error analysis heatmap.
图 9 不同温湿度组合下的冷凝液滴分布与三维指纹重构形貌 (a) 冷凝液滴分布图; (b) 三维指纹重构片段形貌图
Figure 9. Condensed droplet distribution and 3D fingerprint reconstruction morphology: (a) Distribution of condensed water droplets; (b) morphology of 3D fingerprint reconstruction fragment.
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