JIHAD EL SANA

Senior Academic

VML-MOC

Segmenting a multiply oriented and curved handwritten text line dataset

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

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.

Publication language English
Pages 13-18
Publication status Published - 01.09.2019

ASJC Scopus subject areas

Artificial Intelligence
Computer Vision and Pattern Recognition
Signal Processing
Media Technology
Access to Document
10.1109/ICDARW.2019.50109
Other files and links
Link to publication in Scopus