Abstract
Nib calligraphy pattern recognition is the way to convert handwritten nib font into its equivalent machine understandable or readable form. Nib calligraphy pattern recognition is derived from pattern recognition and computer vision, a variety of work has been done on Urdu literature and on Urdu handwritten automatic line segmentation. This research work is based on Urdu Nastaleeq Nib calligraphy pattern recognition. The width of the Qalam (Nib) makes difficulties in recognition due to different width of qalam pattern varieties, so there is dire need to develop a system that can recognize the digitized image of Urdu Nastaleeq Nib font with high accuracy. The objective of this research is to create a ground for the development of an efficient and robust Urdu Optical Character Recognition (OCR) for Urdu Nastaleeq nib pattern recognition and to develop a system that can recognize the digitized image of Urdu Nastaleeq Nib font with high accuracy. Urdu Nastaleeq nib pattern recognition. The research work mainly focuses on identifying the Urdu nib calligraphy pattern recognition. The purpose of the research is to create a system for Urdu Nastaleeq Nib calligraphy pattern recognition to get benefit from the cultural heritage of Nib calligraphic material. The Urdu Nastaleeq Nib Calligraphy Pattern Recognition research work is proposed to be done on the calligraphic Urdu Nastaleeq Nib pattern recognition. This research mainly focuses on recognizing the handwritten Urdu Nastaleeq Nib typeset and eliminating the noise which is the main difficulty in interpretation the font clearly. The aim here is to build up a more consistent, correct and precise system for Urdu Nastaleeq Nib calligraphy Pattern Recognition.
Highlights
The process of converting handwritten and typed characters into machine readable form proceeds in OCR (Optical Character Recognition)
There is a lot of work has been done on Urdu offline, online, typed and handwritten characters but no work has been done on Urdu Nastaleeq Nib pattern recognition so there is dire need of recognizing the nib calligraphy patterns in order to get benefit of the cultural heritage written with Nib
Feed forward neural network used for the categorization of Nastaleeq compound characters the model was created in matlab and it achieved 70% correctness on average
Summary
The process of converting handwritten and typed characters into machine readable form proceeds in OCR (Optical Character Recognition). The Arabic writing system based on thirty alphabets which are easy to recognize but difficult to understandable when they are written by hand. These letters were categorized by supervised neural network. Nastaleeq is a multifaceted font because of its nature They present the clarification that uses Omega as the Typesetting Engine for Mateen Ahmed Abbasi and Adnan Ahmed Abbasi: Urdu Nastaleeq Nib Calligraphy Pattern Recognition rendering Nastaleeq. There is a lot of work has been done on Urdu offline, online, typed and handwritten characters but no work has been done on Urdu Nastaleeq Nib pattern recognition so there is dire need of recognizing the nib calligraphy patterns in order to get benefit of the cultural heritage written with Nib
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