Analysis of off-line handwritten text samples of different gender using shape descriptors

The human experience in the analysis of the handwriting of male and female writers indicates that gender affects the appearance of the handwritten text. These differences are usually very difficult to describe numerically. In order to analyze the handwriting differences between male and female writers, several shape description techniques, such as the tangent angle function, curvature function and Fourier descriptors, were used in this paper. As an additional contribution of the paper, a database of 3766 off-line handwritten cursive and capitalized written words has been created. The database consists of male and female handwriting samples, classified by gender and handedness. The experimental results show that typical attributes of male and female handwritings imply certain differences in shape decriptors, and those differences have the potential for usage in gender handwriting discrimination.