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.
|Number of pages
|IS and T International Symposium on Electronic Imaging Science and Technology
|Published - 2017
|Human Vision and Electronic Imaging 2017, HVEI 2017 - Burlingame, United States
Duration: 29 Jan 2017 → 2 Feb 2017