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Authors: Insaf Setitra ; Zineb Hadjadj and Abdelkrim Meziane

Affiliation: CERIST, Algeria

Keyword(s): Tracking, Connected Components, Angle Minimization, Segmentation, Line, Handwritten, Prediction.

Related Ontology Subjects/Areas/Topics: Applications ; Cardiovascular Imaging and Cardiography ; Cardiovascular Technologies ; Computer Vision, Visualization and Computer Graphics ; Health Engineering and Technology Applications ; ICA, PCA, CCA and other Linear Models ; Image Understanding ; Pattern Recognition ; Signal Processing ; Software Engineering ; Theory and Methods

Abstract: Tracking of objects in videos consists of giving a label to the same object moving in different frames. This labelling is performed by predicting position of the object given its set of features observed in previous frames. In this work, we apply the same rationale by considering each connected component in the manuscript as a moving object and to track it so that to minimize the distance and angle of of the connected component to its nearest neighbour. The approach was applied to images of ICDAR 2013 handwritten segmentation contest and proved to be robust against text orientation, size and writing script.

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Paper citation in several formats:
Setitra, I.; Hadjadj, Z. and Meziane, A. (2017). A Tracking Approach for Text Line Segmentation in Handwritten Documents. In Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-222-6; ISSN 2184-4313, SciTePress, pages 193-198. DOI: 10.5220/0006199001930198

@conference{icpram17,
author={Insaf Setitra. and Zineb Hadjadj. and Abdelkrim Meziane.},
title={A Tracking Approach for Text Line Segmentation in Handwritten Documents},
booktitle={Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2017},
pages={193-198},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006199001930198},
isbn={978-989-758-222-6},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - A Tracking Approach for Text Line Segmentation in Handwritten Documents
SN - 978-989-758-222-6
IS - 2184-4313
AU - Setitra, I.
AU - Hadjadj, Z.
AU - Meziane, A.
PY - 2017
SP - 193
EP - 198
DO - 10.5220/0006199001930198
PB - SciTePress