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Printed Persian Subword Recognition Using Wavelet Packet Descriptors
Joint Authors
Nasrollahi, Samira
Ebrahimi, Afshin
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-11-12
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
In this paper, we present a new approach to offline OCR (optical character recognition) for printed Persian subwords using wavelet packet transform.
The proposed algorithm is used to extract font invariant and size invariant features from 87804 subwords of 4 fonts and 3 sizes.
The feature vectors are compressed using PCA.
The obtained feature vectors yield a pictorial dictionary for which an entry is the mean of each group that consists of the same subword with 4 fonts in 3 sizes.
The sets of these features are congregated by combining them with the dot features for the recognition of printed Persian subwords.
To evaluate the feature extraction results, this algorithm was tested on a set of 2000 subwords in printed Persian text documents.
An encouraging recognition rate of 97.9% is got at subword level recognition.
American Psychological Association (APA)
Nasrollahi, Samira& Ebrahimi, Afshin. 2013. Printed Persian Subword Recognition Using Wavelet Packet Descriptors. Journal of Engineering،Vol. 2013, no. 2013, pp.1-11.
https://search.emarefa.net/detail/BIM-473739
Modern Language Association (MLA)
Nasrollahi, Samira& Ebrahimi, Afshin. Printed Persian Subword Recognition Using Wavelet Packet Descriptors. Journal of Engineering No. 2013 (2013), pp.1-11.
https://search.emarefa.net/detail/BIM-473739
American Medical Association (AMA)
Nasrollahi, Samira& Ebrahimi, Afshin. Printed Persian Subword Recognition Using Wavelet Packet Descriptors. Journal of Engineering. 2013. Vol. 2013, no. 2013, pp.1-11.
https://search.emarefa.net/detail/BIM-473739
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-473739