Genetic Algorithms for Perceptual Codes Extraction

Ltaief, Mahmoud; Njah, Sourour; Bezine, Hala; Alimi, Adel M.

doi:10.4236/jilsa.2012.44026

Cited by 6 publications

(3 citation statements)

References 20 publications

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“…Therefore, each stroke with its curvilinear velocity obeys the Beta-elliptic approach and online script can be segmented into different ones by tracing Beta-elliptic parameters. [18], [19], [20], [21] The Beta function is presented in this equation 1β…”

Section: Beta-elliptic Featuresmentioning

confidence: 99%

Workbook for e-Education: Children’s Online Handwriting Quality Analysis.

Akouaydi¹,

Hamdi²,

Boubaker³

et al. 2021

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<div>This paper describes an innovative e-learning project which is the development of a digital workbook that helps teaching handwriting at school. In this work, we propose a new qualitative and quantitative analysis process of cursive handwriting. This process detects automatically mistakes, gives a real-time feedback and helps teachers evaluate children’s writing skills. The main aim of this digital workbook is to help children learn how to write correctly. The proposed process is composed of five main criteria: shape,direction, stroke order, position respect to the reference lines and kinematics of the trace. It analyzes the handwriting quality and gives automatically feedback based on the Beta-Elliptic Model using similarity detection (SD) and dissimilarity distance (DD) measure. Our work apprehends dynamic and visual representation of the acquired traces and selects efficient features adapted to various handwriting styles and multiple script languages such as Arabic, Latin, digits, and symbols drawing. It demonstrates that beta-elliptic is not only a model for segmentation and recognition but also a tool to evaluate handwriting. Our application offers two interactive interfaces respectively dedicated to learners, and experts or teachers who can adapt it easily to the specificity of each child. The validation of the proposed system is done on a database collected in Tunisia primary schools with 400 children. Experimental results show that the efficiency and robustness of our suggested framework that do help teachers and children by offering positive feedback throughout the handwriting learning process using tactile digital devices.</div>

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Section: Beta-elliptic Featuresmentioning

confidence: 99%

Workbook for e-Education: Children’s Online Handwriting Quality Analysis.

Akouaydi¹,

Hamdi²,

Boubaker³

et al. 2021

Preprint

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“…These basic shapes have been identified as Global Perceptual Codes with GPC "Ain" which only characterize the Arabic script. [18], [19], [23], [24], [25] Thus, in this paper we use only 9 basic perceptual shapes which can form any script. In Figure 1, we notice that handwriting is an arrangement of perceptual codes in a special order, and we can from different scripts with the same group of basic shape such as the two Arabic letter hamza .…”

Section: Segmentation Stepmentioning

confidence: 99%

“…Consequently, each stroke with its curvilinear velocity obeys the Beta-elliptic approach and online script can be segmented into different ones by tracting Beta-elliptic parameters. [19], [20], [24], [28] The Beta function is presented in the equation( 1)…”

Section: Segmentation Stepmentioning

confidence: 99%

Neural Architecture based on Fuzzy Perceptual Representation For Online Multilingual Handwriting Recognition

Akouaydi,

Njah,

Ouarda

et al. 2019

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Due to the omnipresence of mobile devices, online handwritten scripts have become the most important feeding input to smartphones and tablet devices. To increase online handwriting recognition performance, deeper neural networks have extensively been used. In this context, our paper handles the problem of online handwritten script recognition based on extraction features system and deep approach system for sequences classification. Many solutions have appeared in order to facilitate the recognition of handwriting. Accordingly, we used an existent method and combined with new classifiers in order to get a flexible system. Good results are achieved compared to online characters and words recognition system on Latin and Arabic scripts. The performance of our two proposed systems is assessed by using five databases. Indeed, the recognition rate exceeds 98%.

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