Handwriting Quality Evaluation

Kulesh, Victor; Schaffer, Kevin; Sethi, Ishwar K.; Schwartz, Mark H.

doi:10.1007/3-540-44732-6_16

Cited by 13 publications

(6 citation statements)

References 3 publications

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“…It recognized the impact of the overall quality of the document on aesthetic perception and used a dataset that featured characters with uniform shapes. Kulesh et al [14] presented a model that relied on low-level characteristics, including aspect ratio, zerocrossing distributions, and width distributions along the character's height. These attributes were then transformed into high-level feature vectors.…”

Section: -Traditional Approachesmentioning

confidence: 99%

Handwritten Arabic Bills Reader and Recognizer

Sweidan,

Hammam

2024

Journal of Computing and Communication

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In pursuit of Egypt's Vision 2030, which emphasizes the pivotal role of governance within state institutions and society, artificial intelligence (AI) stands as a transformative force. A central tenet of this vision involves harnessing AI technologies to accelerate the digitization of documents and their seamless integration into a unified system. This fosters more informed decision-making processes and revolutionizes processing and utilizing information. Our current research project aligns with this broader goal by deep learning capabilities to support organizations involved in enterprise applications. By incorporating AI-driven solutions, we aim to empower these organizations to manage their operations and optimize resource allocation efficiently. The proposed model eliminates manual input of handwritten invoices into ERP applications, resulting in substantive cost savings. Furthermore, the proposed model integrates an entity classification system enhanced by LSTM, significantly improving invoice data's clarity and accuracy. This streamlined approach saves valuable time and enhances the overall effectiveness of resource allocation and decision-making processes. In essence, by integrating AI into document management and enterprise operations, we are not only contributing to the realization of Egypt's vision but also spearheading a technological transformation that has far-reaching implications for governance, efficiency, and progress in the digital age.

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Section: -Traditional Approachesmentioning

confidence: 99%

Handwritten Arabic Bills Reader and Recognizer

Sweidan,

Hammam

2024

Journal of Computing and Communication

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“…A research [9] used five primitives to evaluate handwriting proficiency of children : legibility, form, alignment, size and space. An educational system [10] is used for handwriting teaching and repair by evaluating the quality of children handwritten letters. Other researchers are exploited the analyzing of children handwriting to identify children with dysgraphia [11].…”

Section: Related Workmentioning

confidence: 99%

Children’s Online Handwriting Quality Analysis.

Akouaydi¹,

Hamdi²,

Boubaker³

et al. 2021

Preprint

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<div>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,</div><div>stroke order and direction.</div>

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“…It is extremely beneficial in terms of the generation of realistic stroke animations of motor actions and the study of dynamic criteria such as direction and order for handwriting learning tools. The problem we tackle here is to quantitatively evaluate a cursive trace with respect to a reference model [25]. In order to be able to teach children how to write, we must be able to analyse their handwriting, to evaluate if the traces are correctly written, and to detail what aspects of the child scripts do not correspond to the teacher models.…”

Section: Comparison Enginementioning

confidence: 99%

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

Akouaydi¹,

Hamdi²,

Boubaker³

et al. 2021

Preprint

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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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Handwriting Quality Evaluation

Cited by 13 publications

References 3 publications

Handwritten Arabic Bills Reader and Recognizer

Handwritten Arabic Bills Reader and Recognizer

Children’s Online Handwriting Quality Analysis.

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

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