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作者机构: BP 1173 Sfax3038 Tunisia B.P. 6072 Gabes Tunisia The Norwegian Colour and Visual Computing Laboratory Department of Computer Science Norwegian University of Science and Technology POBox 191 2802 Norway Department of Electrical and Electronic Engineering Science Faculty of Engineering and the Built Environment University of Johannesburg South Africa
出 版 物:《TechRxiv》 (TechRxiv)
年 卷 期:2021年
核心收录:
主 题:Function evaluation
摘 要:Contributions: An innovative e-learning project is presented in this paper, which is a mobile workbook that teaches handwriting at school. This mobile application proposes a new qualitative and quantitative analysis process of online cursive handwriting. It gives a real-time feedback, detects mistakes and helps teachers evaluate children’s writing skills. The main aim of this notebook is to aid kids learn how to write correctly. We analyze handwriting according to major criteria like shape, kinematics of the trace, position respect to the reference lines, stroke order and direction. Background: Beta-elliptic model with dissimilarity distance (DD) and similarity detection (SD), and SVM with Cartesian Fourier Descriptor Model (FDcarM) are used to analyze the handwriting quality. Our work apprehends dynamic and visual representations of the acquired traces, describes the overall geometry of a trace as a function of the undulations of its curvature function and selects efficient features adapted to various handwriting styles. This work demonstrates that beta-elliptic model is not only a model for segmentation and recognition but also a tool to evaluate handwriting. Intended outcomes: A masterclass environment that motivates childrents to perform better on in application evaluations. The mobile workbook should be positively received by learners and teachers. Application design: Our application provides interfaces for both learners and experts which are flexible with the particularity of each child and makes experienced kids engaged with challenging tasks. Findings: For the validation of our proposed system,we collected a database of 400 Tunisian children from pre-schools and primary schools. Results demonstrate the efficiency and robustness of our application an the great majority of expertts expressed a positive attitude toward it. © 2021, CC BY.