Handwriting style classification

Abstract

This paper describes an independent handwriting style classifier that has been designed to select the best recognizer for a given style of writing. For this purpose a definition of handwriting legibility has been defined and a method has been implemented that can predict this legibility. (legible/illegible), 65.5% (legible/middle) and 90.5% (middle/illegible) correct classification for two classes. For the three-classes legibility classification the rate of correct classification is 67.33% using PNN classifier.

Text independent writer recognition using redundant writing patterns with contour-based orientation and curvature features

“…In case of handwritten document images, these directional features and their improved variants have been successfully applied to character/word recognition [44][45][46][47] as well as classification of writing styles [48]. Since the handwritten characters issued by a particular writer can be regarded as having a specific shape/style, chain code based features are likely to work well on tasks like writer recognition as well.…”

A Study on Farsi Handwriting Styles for Online Recognition

“…Writing styles and individuality can be used for handwriting classification [25], writer verification and identification [26], and examining forensic documents [27]. In this paper, styles and varieties of online Farsi handwriting are studied and analyzed on TMU-OFS dataset.…”