Advanced Tamil Character Recognition using Generative Adversarial Networks and Augmented Reality

This system on an advanced Tamil character recognition theme uses the benefit of FPGA-based acceleration for gaining the enhancement of high-performance processing, keeping it scalable. What makes such a system interesting is achieving recognition of Tamil text being 3D carvings or embossed inside monuments with an adequate preservation of cultural heritage material. As an added theme, its support to multiscript recognitions-Tamil, Hindi, English and others-would enable it smoothly multilingually be well-integrated into a vast variety of applications. The integration of AR enhances user interaction as it superimposes live recognition results onto the physical object and also provides an immersive learning experience along with hands-on guidance. The architecture of CNNs and GANs used in data augmentation can make this system reliable for recognition across diverse ranges of writing styles, fonts, and languages. It happens to be an ideal tool that fulfils the demands of state-of-the-art Optical Character Recognition (OCR), interpretation of 3D texts, educational applications, as well as real-time multi-lingual functionalities while facing contemporary demands in text digitization.

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Publication Details

Published
2025-03-28
DOI
https://doi.org/10.1109/icdsaai65575.2025.11011774
Primary Topic
Handwritten Text Recognition Techniques
Type
article
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article

Advanced Tamil Character Recognition using Generative Adversarial Networks and Augmented Reality

G Subhashini, S. T., G Mahalaksmi, K Sundarraj
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Handwritten Text Recognition Techniques
article

Advanced Tamil Character Recognition using Generative Adversarial Networks and Augmented Reality

G Subhashini, S. T., G Mahalaksmi, K Sundarraj
article en

Abstract

This system on an advanced Tamil character recognition theme uses the benefit of FPGA-based acceleration for gaining the enhancement of high-performance processing, keeping it scalable. What makes such a system interesting is achieving recognition of Tamil text being 3D carvings or embossed inside monuments with an adequate preservation of cultural heritage material. As an added theme, its support to multiscript recognitions-Tamil, Hindi, English and others-would enable it smoothly multilingually be well-integrated into a vast variety of applications. The integration of AR enhances user interaction as it superimposes live recognition results onto the physical object and also provides an immersive learning experience along with hands-on guidance. The architecture of CNNs and GANs used in data augmentation can make this system reliable for recognition across diverse ranges of writing styles, fonts, and languages. It happens to be an ideal tool that fulfils the demands of state-of-the-art Optical Character Recognition (OCR), interpretation of 3D texts, educational applications, as well as real-time multi-lingual functionalities while facing contemporary demands in text digitization.

St. Joseph's Institute of Technology (IN)
Openalex Percentile: Top 90%
Handwritten Text Recognition Techniques
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