Signature verification is a critical task in many applications, including forensic science, legal judgments, and financial markets. However, current signature verification systems are often difficult to explain, which can limit their acceptance in these applications. In this paper, we propose a novel explainable offline automatic signature verifier (ASV) to support forensic handwriting examiners. Our ASV is based on a universal background model (UBM) constructed from offline signature images. It allows us to assign a questioned signature to the UBM and to a reference set of known signatures using simple distance measures. This makes it possible to explain the verifier's decision in a way that is understandable to non experts. We evaluated our ASV on publicly available databases and found that it achieves competitive performance with state of the art ASVs, even when challenging 1 versus 1 comparison are considered. Our results demonstrate that it is possible to develop an explainable ASV that is also competitive in terms of performance. We believe that our ASV has the potential to improve the acceptance of signature verification in critical applications such as forensic science and legal judgments.

翻译：签名验证是众多应用中的关键任务，包括法庭科学、法律判决和金融市场等。然而，当前的签名验证系统往往难以解释，这限制了其在上述应用中的接受度。本文提出了一种新颖的可解释离线自动签名验证器（ASV），以支持司法笔迹鉴定人。我们的ASV基于从离线签名图像构建的通用背景模型（UBM），通过简单的距离度量，可将待鉴别签名归入UBM及已知签名的参考集。这使得验证器的决策结果能够以非专业人士可理解的方式加以解释。我们在公开数据库上评估了该ASV，发现即便在具有挑战性的1对1比对场景中，其性能仍与当前最先进的ASV不相上下。实验结果表明，开发兼具可解释性与竞争性性能的ASV是可行的。我们相信，该ASV有望提升签名验证在法庭科学和法律判决等关键应用中的接受度。