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India Handwritten Digits Recognition

Iklaas Sultan · University of Mosul, College of Education for Pure Science · 2009

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Author / responsible party
Iklaas Sultan
Publisher
University of Mosul, College of Education for Pure Science
Year
2009
ISSN
1812-125X
ISSN
1812-125X
Language
English
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Abstract<br /> An Optical Character Recognition (OCR) approach for handwritten Indian digit is presented in this paper, by using the proposed sector approach. In this approach, the normalized and thinned digit image is divided into sectors with each sector covering a fixed angle. The features totaling 24 include vector distances, angles. For recognition, the K-Nearest-Neighbours classifier is used. This method was tested using 45 patterns for each digit with different writers. The sample images were divided into 20 training and 25 test images. Images in the test set did not appear in the training sets. This method performs extremely well with recognition rates 82.8%. This is a very good performance.

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APA 7

Sultan, I. (2009). India Handwritten Digits Recognition. https://doi.org/10.33899/edusj.2009.57436

MLA

Sultan, Iklaas. "India Handwritten Digits Recognition." 2009. https://doi.org/10.33899/edusj.2009.57436.

Chicago

Sultan, Iklaas. 2009. "India Handwritten Digits Recognition.". https://doi.org/10.33899/edusj.2009.57436.

Harvard

Sultan, I. 2009, India Handwritten Digits Recognition, University of Mosul, College of Education for Pure Science, available at: https://doi.org/10.33899/edusj.2009.57436 [Accessed 7 Aug. 2026].

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Title
India Handwritten Digits Recognition
Author / contributors
Iklaas Sultan
Publisher
University of Mosul, College of Education for Pure Science
Publication year
2009
ISSN
1812-125X
ISSN
1812-125X
Language
English

Subjects

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india handwritten; digits recognition; optical character recognition
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