TY - JOUR
T1 - VML-MOC
T2 - Segmenting a multiply oriented and curved handwritten text line dataset
AU - Barakat, Berat Kurar
AU - Cohen, Rafi
AU - El-Sana, Jihad
AU - Rabaev, Irina
PY - 2019/11
Y1 - 2019/11
N2 - 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.
AB - 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.
U2 - 10.1109/ICDARW.2019.50109
DO - 10.1109/ICDARW.2019.50109
M3 - Article
SN - 1520-5363
SP - 13
EP - 18
JO - Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
JF - Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
ER -