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Ancient Character Recognition: A Comprehensive Review

Krithiga, R ; Varsini, SR ; Gabriel Joshua, R ; Om Kumar, C U

IEEE access, 2023, p.1-1 [Periódico revisado por pares]

IEEE

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  • Título:
    Ancient Character Recognition: A Comprehensive Review
  • Autor: Krithiga, R ; Varsini, SR ; Gabriel Joshua, R ; Om Kumar, C U
  • Assuntos: Character recognition ; Character Segmentation ; Complexity theory ; Computer Vision ; Deep learning ; Feature extraction ; Handwritten text pre-processing ; Image processing ; Image segmentation ; Optical character recognition ; Task analysis ; Text processing
  • É parte de: IEEE access, 2023, p.1-1
  • Descrição: Deep learning-based character recognition of Tamil inscriptions plays a significant role in preserving the ancient Tamil language. The complexity of the task lies in the precise classification of the age-old Tamil letters (Vattezhuthu) into modern-day Tamil letter structures. Various methodologies and pre-processing techniques have been used for denoising the ancient Tamil manuscript to retrieve the Tamil text. Researchers have used various synthesized and scanned images of stone wall inscriptions, palm leaves manuscripts, and offline handwritten characters for their analysis. Over the years, Ancient Tamil scripts have deteriorated with time due to various natural calamities. Strong denoising and feature extraction methods are required to separate the letters accurately to tackle this issue. Techniques such as CNN(OCR), ResNet, SVM, KNN, HorVer method, etc., are utilized to digitize Tamil characters. This technique has successfully converted handwritten characters into digitalized text for multiple languages, including Tamil, Arabic, English, Latin, Chinese, German, etc. Different models have been evaluated based on their segmentation and recognition rates, accuracy, detection rate, precision, and confusion matrix. This paper will concentrate on Ancient Tamil character segmentation and recognition models. Besides, we will give an overview of the different models and datasets available. Lastly, we summarise the key challenges and the future scope related to the topic.
  • Editor: IEEE
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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