IEEE Trans Pattern Anal Mach Intell. 2014 Dec;36(12):2452-65. doi: 10.1109/TPAMI.2014.2330609.
Latent fingerprints serve as an important source of forensic evidence in a court of law. Automatic matching of latent fingerprints to rolled/plain (exemplar) fingerprints with high accuracy is quite vital for such applications. However, latent impressions are typically of poor quality with complex background noise which makes feature extraction and matching of latents a significantly challenging problem. We propose incorporating top-down information or feedback from an exemplar to refine the features extracted from a latent for improving latent matching accuracy. The refined latent features (e.g. ridge orientation and frequency), after feedback, are used to re-match the latent to the top K candidate exemplars returned by the baseline matcher and resort the candidate list. The contributions of this research include: (i) devising systemic ways to use information in exemplars for latent feature refinement, (ii) developing a feedback paradigm which can be wrapped around any latent matcher for improving its matching performance, and (iii) determining when feedback is actually necessary to improve latent matching accuracy. Experimental results show that integrating the proposed feedback paradigm with a state-of-the-art latent matcher improves its identification accuracy by 0.5-3.5 percent for NIST SD27 and WVU latent databases against a background database of 100k exemplars.
潜在指纹是法庭法医学证据的重要来源。自动将潜在指纹与滚动/平面（示例）指纹高精度匹配对于此类应用至关重要。然而，潜在指纹的质量通常较差，背景噪声复杂，这使得潜在指纹的特征提取和匹配成为一个极具挑战性的问题。我们建议从示例中引入自上而下的信息或反馈，以改进从潜在指纹中提取的特征，从而提高潜在指纹匹配的准确性。反馈后，经过精炼的潜在特征（例如脊线方向和频率）用于重新将潜在指纹与基线匹配器返回的前 K 个候选示例进行匹配，并对候选列表进行排序。本研究的贡献包括：（i）设计系统的方法来利用示例中的信息来改进潜在特征，（ii）开发反馈范例，可以将其包装在任何潜在匹配器周围，以提高其匹配性能，以及（iii）确定何时反馈实际上是提高潜在匹配准确性所必需的。实验结果表明，将所提出的反馈范例与最先进的潜在匹配器集成，可以将 NIST SD27 和 WVU 潜在数据库与 10 万示例背景数据库的识别准确率提高 0.5-3.5%。
