In this article we demonstrate how to obtain the ultimate lateral resolution in surface plasmon microscopy (SPM) (diffraction limited by the objective). Surface plasmon decay lengths are determined theoretically and experimentally, for wavelengths ranging from 531 to 676 nm, and are in good agreement. Using these values we can determine for each particular situation which wavelength should be used to obtain an optimal lateral resolution, i.e., where the plasmon decay length does not limit the resolution anymore. However, there is a trade‐off between thickness resolution and lateral resolution in SPM. Because of the non‐optimal thickness resolution, we use several techniques to enhance the image acquisition and processing. Without these techniques the use of short wavelengths results in images where the contrast has vanished almost completely. In an example given, a 2.5 nm SiO₂ layer on a gold layer is imaged with a lateral resolution of 2 μm, and local reflectance curves are measured to determine the layer thickness. The SPM image is compared with an atomic force microscopy image of the same object. We obtain a 3 μm resolution when thickness differences within a lipid monolayer are imaged and measured.

The Netherlands Forensic Institute and the Institute for Forensic Science in Shanghai are in search of a signature verification system that can be implemented in forensic casework and research to objectify results. We want to bridge the gap between recent technological developments and forensic casework. In collaboration with the German Research Center for Artificial Intelligence we have organized a signature verification competition on datasets with two scripts (Dutch and Chinese) in which we asked to compare questioned signatures against a set of reference signatures. We have received 12 systems from 5 institutes and performed experiments on online and offline Dutch and Chinese signatures. For evaluation, we applied methods used by Forensic Handwriting Examiners (FHEs) to assess the value of the evidence, i.e., we took the likelihood ratios more into account than in previous competitions. The data set was quite challenging and the results are very interesting.