Multi-Criteria Handwriting Quality Analysis with Online Fuzzy Models

Damien Simonnet (1, 2) , Eric Anquetil (1, 2) , Manuel Bouillon (1, 2)

1 INSA Rennes - Institut National des Sciences Appliquées - Rennes
2 IntuiDoc - intuitive user interaction for document

IntuiScript is an innovative project aiming at the development of a digital workbook providing feedback during the handwriting learning process for children from three to seven years old. In this context, the paper presents a method to analyse handwriting quality that responds to the expectations of the IntuiScript educational scenario: on-line and real time feedback for children, an automatic detection of children mistakes guiding the pedagogical progression, and a precise analysis of children writing saved to help teacher to understand children writing skills. The presented method introduces a multi-criteria architecture to analyse handwriting quality based on three different aspects: shape, order and direction. The validation of the proposed approach is done on a realistic dataset collected in preschools and primary schools with 952 children. Results show a positive feedback of children and teachers about the use of tactile digital devices, and a significant improvement of the performances of the multi-criteria architecture compared to the previous analyser. The ground truth has been annotated by experts with different levels of confidence. Specific evaluation metrics are introduced to deal with confidence annotations.

Mots clés: Handwriting Analysis; Pen-Based Interaction; Educational System

Domaines: Intelligence artificielle [cs.AI]

Damien Simonnet, Eric Anquetil, Manuel Bouillon. Multi-Criteria Handwriting Quality Analysis with Online Fuzzy Models. Pattern Recognition, 2017, 69, pp.310-324. ⟨10.1016/j.patcog.2017.04.003⟩. ⟨hal-01515397⟩