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Pattern Analysis and Applications

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16-09-2019 | Short paper

Segmentation of handwritten words using structured support vector machine

Authors: Manoj Kumar Sharma, Vijaypal Singh Dhaka

Published in: Pattern Analysis and Applications | Issue 3/2020

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Abstract

Words and characters segmentation is a most indispensable and fundamental task for the handwritten script recognition. However, the complex language structures, deviation in pen breadth and slant in inscription make the feature extraction process very challenging. In this research, a binary quadratic process has been formulated for the word segmentation. It deliberates a co-relationship between the inter-word gap and intra-word gap. The structured support vector machine is used for the experiment. Experimental results of public datasets (i.e., ICDAR2009 and ICDAR2013) show state-of-the-art performance of the designed algorithm.

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Title: Segmentation of handwritten words using structured support vector machine
Authors: Manoj Kumar Sharma
Vijaypal Singh Dhaka
Publication date: 16-09-2019
Publisher: Springer London
Published in: Pattern Analysis and Applications / Issue 3/2020
Print ISSN: 1433-7541
Electronic ISSN: 1433-755X
DOI: https://doi.org/10.1007/s10044-019-00843-x

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