Forensic Analysis of Manuscript Authorship: An Optimized Computational Approach Based on Texture Descriptors

This paper presents an optimized method for establishing the authorship of questioned handwritten documents, on the basis of a forensic analysis and a computational model using texture descriptors. The proposed method uses two classes of texture descriptors: model-based, using fractal geometry, and statistical, using GLCM (Gray-Level Co-occurrence Matrix) and Haralick’s descriptors. The proposed method also uses an SVM (Support Vector Machine) as a classifier and generator of the writer-independent training. The results demonstrate the robustness of the writer-independent obtained from the features by using texture descriptors and robustness in the amount low of samples used as references for comparison and the number of feature used. The results appear promising, in the order of 97.7 %, and are consistent with those obtained in other studies that used the same database.