A Potrace-Based Algorithm for Extracting Handwriting Line Spacing, Baseline, and Slant

Handwriting can reveal the writer's personality traits, which explains the interest in systems for its automated analysis. Such systems require image collection and preprocessing, feature extraction, and personality classification. Feature extraction is usually done by processing raster images. A few publications deal with vectorized handwriting images, but none use the Potrace algorithm and Bezier curves. We propose a modified Potrace algorithm for computing handwriting line spacing, baseline, and slant. The proposed algorithm is applicable for processing skewed texts and can be used to reduce input data complexity for other feature extraction techniques.