VML-MOC: Segmenting a multiply oriented and curved handwritten text lines dataset

Berat Kurar Barakat, Rafi Cohen, Irina Rabaev, Jihad El-Sana

Research output: Working paper/PreprintPreprint

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Abstract

This paper publishes a natural and very complicated dataset of handwritten documents with multiply oriented and curved text lines, namely VML-MOC dataset. These text lines were written as remarks on the page margins by different writers over the years. They appear at different locations within the orientations that range between 0 and 180 or as curvilinear forms. We evaluate a multi-oriented Gaussian based method to segment these handwritten text lines that are skewed or curved in any orientation. It achieves a mean pixel Intersection over Union score of 80.96% on the test documents. The results are compared with the results of a single-oriented Gaussian based text line segmentation method.
Original languageEnglish GB
StatePublished - 2021

Publication series

NamearXiv PrePrint,

Keywords

  • Computer Science - Computer Vision and Pattern Recognition

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