Affiliation:
1. Birla Institute of Technology, Ranchi, India
Abstract
In recent years, many information retrieval, character recognition, and feature extraction methodologies in Devanagari and especially in Hindi have been proposed for different domain areas. Due to enormous scanned data availability and to provide an advanced improvement of existing Hindi automated systems beyond optical character recognition, a new idea of Hindi printed and handwritten document classification system using support vector machine and fuzzy logic is introduced. This first pre-processes and then classifies textual imaged documents into predefined categories. With this concept, this article depicts a feasibility study of such systems with the relevance of Hindi, a survey report of statistical measurements of Hindi keywords obtained from different sources, and the inherent challenges found in printed and handwritten documents. The technical reviews are provided and graphically represented to compare many parameters and estimate contents, forms and classifiers used in various existing techniques.
Reference87 articles.
1. Generalization of Hindi OCR Using Adaptive Segmentation and Font Files
2. Coarse classification of handwritten Hindi characters.;P.Agrawal;International Journal of Advanced Science and Technology,2009
3. Ligature analysis-based Urdu OCR framework.;Z.Ahmed;International Conference on Frontiers of Information Technology,2017
4. UOCR: A ligature based approach for an Urdu OCR system.;T.Ali;3rd International Conference on Computing for Sustainable Global Development,2016
5. Combining Multiple Feature Extraction Techniques for Handwritten Devnagari Character Recognition
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