Review on MODI Script Character Recognition Using Deep Learning Techniques

The MODI script, a historic Indian script with limited use in administrative activities from the 17th to 19th centuries, is highly challenging for character recognition systems. The MODI script characters are dissimilar, have intricate structures, and exist with different handwriting patterns, hence rendering automatic identification cumbersome. Despite the limitations, some machine learning, especially deep learning, methods have been utilized to recognize MODI scripts accurately in recent years. This review investigates the uses of convolutional neural networks (CNNs), transfer learning models such as VGG16 and ResNet, and mixed architectures fusing CNN with Support Vector Machines (SVM). We discuss these methods' methodologies, advantages, and disadvantages, explain challenges concerning dataset insufficiency and handwriting diversity, and propose possible future studies to enhance recognition systems. This article emphasizes the importance of automated MODI script recognition in preserving and making historical documents accessible..

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Publication Details

Journal
International Journal of Advanced Research in Science Communication and Technology
Published
2025-04-17
DOI
https://doi.org/10.48175/ijarsct-25318
Primary Topic
Handwritten Text Recognition Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Review on MODI Script Character Recognition Using Deep Learning Techniques

Brijendra Gupta, Mrunali Manohar Bhong
International Journal of Advanced Research in Science Communication and Technology
Handwritten Text Recognition Techniques
article

Review on MODI Script Character Recognition Using Deep Learning Techniques

Brijendra Gupta, Mrunali Manohar Bhong
article en

Abstract

The MODI script, a historic Indian script with limited use in administrative activities from the 17th to 19th centuries, is highly challenging for character recognition systems. The MODI script characters are dissimilar, have intricate structures, and exist with different handwriting patterns, hence rendering automatic identification cumbersome. Despite the limitations, some machine learning, especially deep learning, methods have been utilized to recognize MODI scripts accurately in recent years. This review investigates the uses of convolutional neural networks (CNNs), transfer learning models such as VGG16 and ResNet, and mixed architectures fusing CNN with Support Vector Machines (SVM). We discuss these methods' methodologies, advantages, and disadvantages, explain challenges concerning dataset insufficiency and handwriting diversity, and propose possible future studies to enhance recognition systems. This article emphasizes the importance of automated MODI script recognition in preserving and making historical documents accessible..

International Journal of Advanced Research in Science Communication and Technology
Openalex Percentile: Top 94%
Handwritten Text Recognition Techniques
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Review on MODI Script Character Recognition Using Deep Learning Techniques — Brijendra Gupta, Mrunali Manohar Bhong · International Journal of Advanced Research in Science Communication and Technology (2025) | TGRS Research Map | TGRS