@inproceedings{57627722d06b45319448cea40b28f890,
title = "Word spotting for handwritten Arabic documents using Harris detector",
abstract = "This paper attempts to deal with the problems of query-by-example word spotting in handwritten Arabic document. This operation needs a lot of time and effort to do manual work. For this, we propose a fully non supervised methodology dedicated to the word spotting system, without using any text word or line segmentation step, because any segmentation errors of the document affect the subsequent word representations and matching steps. This work is addressing by using a method that integrates two steps into one. First the interest points are automatically extracted from the images. Then, the matching of the extracted points is established with a correlation technique combined to a relaxation technique. Validation study is conducted under a series of controlled experiments on handwritten Arabic document images.",
keywords = "Handwritten Arabic document, Harris corner interest points, Relaxation technique, Zero mean Normalized Cross Correlation (ZNCC), word spotting",
author = "Youssef Elfakiri and Ghizlane Khaissidi and Mostafa Mrabti and Driss Chenouni and Yacoubi, \{Mounim El\}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; International Conference on Information Technology for Organizations Development, IT4OD 2016 ; Conference date: 30-03-2016 Through 01-04-2016",
year = "2016",
month = may,
day = "25",
doi = "10.1109/IT4OD.2016.7479291",
language = "English",
series = "2016 International Conference on Information Technology for Organizations Development, IT4OD 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Younes Lakhrissi and Adil Kenzi and Hakim Bendjenna and Nfaoui, \{El Habib\}",
booktitle = "2016 International Conference on Information Technology for Organizations Development, IT4OD 2016",
}