Effective Printed Tamil Text Segmentation and Recognition Using Bayesian Classifier

Manisha, S.; Sharmila, T. Sree

doi:10.1007/978-981-10-3874-7_69

Cited by 2 publications

(1 citation statement)

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“…Nearest Neighbourhood classifier calculates the Euclidian distance between test image and each of the training images to select the label of nearest neighbour as predicted class [29], [56]. Other than distance metrics, probability of the features are also used to predict the class label of the image using Bayesian classifier [57], [58]. Unlike a decision tree, multiple decision trees are combined to improve the recognition rate in gradient boosting tree classifier [41].…”

Section: E Classificationmentioning

confidence: 99%

Ancient Character Recognition: A Comprehensive Review

Krithiga,

Varsini,

Gabriel Joshua

et al. 2023

IEEE Access

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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.

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