The authors present a new method of writer identification, employing the full power of multiple experiments, which yields a statistically significant result. Each individual binarized and segmented character is represented as a histogram of 512 binary pixel patterns— 3 × 3 black and white patches. In the process of comparing two given inscriptions under a "single author" assumption, the algorithm performs a Kolmogorov–Smirnov test for each letter and each patch. The resulting p-values are combined using Fisher's method, producing a single p-value. Experiments on both Modern and Ancient Hebrew data sets demonstrate the excellent performance and robustness of this approach. © 2017 Society for Imaging Science and Technology.
Arie Shaus, Eli Turkel, "Writer Identification in Modern and Historical Documents via Binary Pixel Patterns, Kolmogorov–Smirnov Test and Fisher's Method" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Human Vision and Electronic Imaging, 2017, pp 203 - 211, https://doi.org/10.2352/ISSN.2470-1173.2017.14.HVEI-144