A Survey on Tamil Handwritten Character Recognition using OCR Techniques

Raj, M. Antony Robert

doi:10.5121/csit.2012.2213

Cited by 9 publications

(1 citation statement)

References 18 publications

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“…Identifying and extracting features from Tamil writings become a more challenging task as the Tamil alphabets are more multifaceted in nature. When compared to western scripts and other Indian scripts, Tamil scripts exhibit a large number of classes, stroke order variation and two-dimensional nature [1]. Tamil language covers massive amount of character sets which has more challenging patterns like loops, crossing, junction, different directions and so on.…”

Section: Introductionmentioning

confidence: 99%

Linear Kernel with Weighted Least Square Regression Co-efficient for SVM Based Tamil Writer Identification

Tharmalingam¹,

Vijayakumar²

2019

IJRTE

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Tamil writer identification is the task of identifying writer based on their Tamil handwriting. Our earlier work of this research based on SVM implementation with linear, polynomial and RBF kernel showed that linear kernel attains very low accuracy compared to other two kernels. But the observation shows that linear kernel performs faster than the other kernels and also it shows very less computational complexity. Hence, a modified linear kernel is proposed to enrich the performance of the linear kernel in recognizing the Tamil writer. Weighted least square parameter estimation method is used to estimate the weights for the dot products of the linear kernel. SVM implementation with modified linear kernel is carried out on different text images of handwriting at character, word and paragraph levels. Comparing the performance with linear kernel, the modified kernel with weighted least square parameter reported promising results.

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Section: Introductionmentioning

confidence: 99%