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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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 0º and 180º 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
StatePublished - 19 Jan 2021


  • Computer Science - Computer Vision and Pattern Recognition


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