Indian Journal of Science and Technology
DOI: 10.17485/ijst/2015/v8i35/86807
Year: 2015, Volume: 8, Issue: 35, Pages: 1-9
Original Article
Ankur Rana1* and Gurpreet Singh Lehal 2
1 Department of Computer Engineering, Punjabi University, Patiala - 147002, Punjab, India; [email protected]
2 Department of Computer Science, Punjabi University, Patiala - 147002, Punjab, India; [email protected]
There are two most popular writing styles of Urdu i.e. Naskh and Nastaliq. Considering Arabic OCR research, ample amount of work has been done on Naskh writing style; focusing on Urdu, which uses Arabic character set commonly used Nastaliq writing style.Due toNastaliq writing style,UrduOCR poses many distinct challenges like compactness, diagonal orientation and context character shape sensitivity etc., for OCR system to correctly recognize the Urdu text image. Due to compactness and slanting nature of Nastaliq writing style, existing methods for Naskh style would not give desirable results. Therefore, in this paper, we are presenting ligature based segmentation OCR system for Urdu Nastaliq script. We have discussed in detail various unique challenges for the Urdu OCR and different feature extraction techniques for Ligature recognition using SVM and kNN classifier. The system is trained to recognize 11,000 Urdu ligatures. We have achieved overall 90.29% accuracy tested on Urdu text images.
Keywords: Feature Extraction (DCT, Directional, Gabor and Gradient), K-Nearest Neighbor, SVM, Urdu OCR
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