Segmentation Based Urdu Nastalique OCR
نویسندگان
چکیده
Urdu Language is written in Nastalique writing style, which is highly cursive, context sensitive and is difficult to process as only the last character in its ligature resides on the baseline. This paper focuses on the development of OCR using Hidden Markov Model and rule based post-processor. The recognizer gets the main body (without diacritics) as input and recognizes the corresponding ligature. Accuracy of the system is 92.73% for printed and then scanned document images at 36 font size.
منابع مشابه
Segmentation of Nastaliq Script for OCR
In this paper we have presented a novel segmentation technique for the implementation of an OCR (Optical Character Recognition) for printed Nastalique text, a calligraphic style of Urdu which uses the Arabic script for its writing. OCR for many of the world major languages have been developed and are being used but at present an OCR for Nastalique is not available and the published research on ...
متن کاملDiacritics Recognition Based Urdu Nastalique OCR System
Improvements and new developments in the field of Artificial Intelligence have opened new horizons in the advancement of machines that originally have limited intelligence. As compared to human brain, machines have already better computational speed and storage however there is still much room to improve the capability to acquire and process data and draw conclusions from it on its own. Optical...
متن کاملRecognition of Urdu Character with Hmm Technique
This paper deals with an Optical Character Recognition system for printed Urdu, a popular Pakistani/Indian script and is the third largest understandable language in the world, especially in the subcontinent but fewer efforts are made to make it understandable to computers. Lot of work has been done in the field of literature and Islamic studies in Urdu, which has to be computerized. Research h...
متن کاملA Finite State Model for Urdu Nastalique Optical Character Recognition
Finite state technology is being used since long to model NLP (Natural Language Processing) applications specially it has very successfully applied to machine translation and speech recognition systems. Character recognition in cursive scripts or handwritten Latin script also have attracted researchers’ attention and some research is also done in this area. Optical character recognition is the ...
متن کاملWord Segmentation for Urdu OCR System
This paper presents a technique for Word segmentation for the Urdu OCR system. Word segmentation or word tokenization is a preliminary task for understanding the meanings of sentences in Urdu language processing. Several techniques are available for word segmentation in other languages but not much work has been done for word segmentation of Urdu Optical Character Recognition (OCR) System. A me...
متن کامل