@inproceedings{fb058c1eb98849a3b814284c414450b1,
title = "PCA-based Arabic Character feature extraction",
abstract = "In this paper we propose two level recognition processes for Arabic Characters. Arabic fonts are connected in nature and thus require segmentation for recognition. Document images are segmented into lines, words or subwords and then characters. In the proposed approach, recognition is applied at two levels with different strategies. First level recognition is applied after 'words' segmentation to recognize isolated characters while second level recognition is applied to segmented characters. The proposed scheme is tested on different font systems which yielded a recognition rate of about 90\%.",
keywords = "Arabic character recognition, PCA",
author = "Abdelmalek Zidouri",
year = "2007",
doi = "10.1109/ISSPA.2007.4555437",
language = "English",
isbn = "1424407796",
series = "2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Proceedings",
booktitle = "2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Proceedings",
}