Multiply oriented and curved handwritten text line dataset (VML-MOC)
curved and skewed text lines, Arabic historical documents, historical documents
VML-MOC (Visual Media Lab - Multiply Oriented and Curved)  is a natural handwritten benchmark dataset for heavily skewed and curved text lines. 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.
VML-MOC dataset document images purely contain binarized side notes. Hence, the researchers can focus only on text line extraction of multiply oriented and curved text lines, devoid of dealing with the challenges of page segmentation, heterogeneity of side text and main text areas and binarization defects.
The dataset consists of 30 document images devided into train (20 pages) and test (10 pages) sets.
The ground truth is provided in three forms: raw pixel labeling, DIVA pixel labeling and PAGE xml file.
 B.Kurar, Rafi Cohen, I. Rabaev, and J. El-Sana VML-MOC: Segmenting a multiply oriented and curved handwritten text lines dataset. In the 3rd International workshop on Arabic and derived Script Analysis and Recognition (ASAR), pp. 13 - 18, 2019. (PDF)