Latent fingerprints are among the most important and widely used evidence in crime scenes, digital forensics and law enforcement worldwide. Despite the number of advancements reported in recent works, we note that significant open issues such as independent benchmarking and lack of large-scale evaluation databases for improving the algorithms are inadequately addressed. The available databases are mostly of semi-public nature, lack of acquisition in the wild environment, and post-processing pipelines. Moreover, they do not represent a realistic capture scenario similar to real crime scenes, to benchmark the robustness of the algorithms. Further, existing databases for latent fingerprint recognition do not have a large number of unique subjects/fingerprint instances or do not provide ground truth/reference fingerprint images to conduct a cross-comparison against the latent. In this paper, we introduce a new wild large-scale latent fingerprint database that includes five different acquisition scenarios: reference fingerprints from (1) optical and (2) capacitive sensors, (3) smartphone fingerprints, latent fingerprints captured from (4) wall surface, (5) Ipad surface, and (6) aluminium foil surface. The new database consists of 1,318 unique fingerprint instances captured in all above mentioned settings. A total of 2,636 reference fingerprints from optical and capacitive sensors, 1,318 fingerphotos from smartphones, and 9,224 latent fingerprints from each of the 132 subjects were provided in this work. The dataset is constructed considering various age groups, equal representations of genders and backgrounds. In addition, we provide an extensive set of analysis of various subset evaluations to highlight open challenges for future directions in latent fingerprint recognition research.

翻译：潜在指纹是全球犯罪现场、数字取证和执法领域中最重要且广泛使用的证据之一。尽管近年来的研究报告了许多进展，但我们注意到，诸如独立基准测试和缺乏大规模评估数据库以改进算法等重大开放问题仍未得到充分解决。现有数据库大多属于半公开性质，缺乏野生环境下的采集和后处理流程。此外，它们无法代表类似真实犯罪现场的逼真捕获场景，从而对算法的鲁棒性进行基准测试。再者，现有的潜在指纹识别数据库缺乏大量独特对象/指纹实例，或无法提供用于与潜在指纹进行交叉比对的地面真值/参考指纹图像。本文介绍了一个新型大规模野生潜在指纹数据库，包含五种不同的采集场景：来自（1）光学和（2）电容式传感器的参考指纹，（3）智能手机指纹，以及从（4）墙面、（5）iPad表面和（6）铝箔表面捕获的潜在指纹。该新数据库包含在上述所有设置下采集的 1,318 个独特指纹实例。本文提供了来自光学和电容式传感器的 2,636 个参考指纹、来自智能手机的 1,318 张手指照片，以及来自 132 个对象的各 9,224 个潜在指纹。数据集构建时考虑了不同年龄组、性别和背景的均衡代表性。此外，我们提供了多种子集评估的广泛分析，以突出潜在指纹识别研究未来方向中的开放挑战。