Radon transform and dynamic programming for the Persian handwritten zip code recognition Online publication date: Wed, 02-Nov-2016
by Jamal Ghasemi; Mohammad Sefidgarnia Amiri; Reza Ghaderi; Jalil Rasekhi
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 15, No. 4, 2016
Abstract: Pattern recognition is one of the major research areas in computer sciences. Optical character recognition (OCR) as one of the pattern recognition topics has specifically attracted the interests of many researchers. This paper presents a method for offline Persian numeral character recognition. It uses Radon transform for feature extraction and a combination of dynamic programming with K-nearest neighbour (KNN) for its recognition task. For the simulations, the Persian postal zip code database of 800 samples has been employed, providing a recognition accuracy of 94.1%.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Intelligent Systems Technologies and Applications (IJISTA):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com