Glyph-based recognition of offline handwritten Telugu characters: GBRoOHTC
| Autor: | Ch. N. Manisha, E. Sreenivasa Reddy, Y. K. Sundara Krishna |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Computer science
Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Computational intelligence 0102 computer and information sciences 02 engineering and technology Glyph computer.software_genre 01 natural sciences Telugu 0202 electrical engineering electronic engineering information engineering ComputingMethodologies_COMPUTERGRAPHICS business.industry Pattern recognition language.human_language ComputingMethodologies_PATTERNRECOGNITION 010201 computation theory & mathematics Handwriting recognition language Classification methods 020201 artificial intelligence & image processing Artificial intelligence business computer Character recognition Natural language processing |
| Zdroj: | 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC). |
| DOI: | 10.1109/iccic.2016.7919567 |
| Popis: | Recognizing offline handwritten Telugu characters from digitized document images is very challenging. In this paper, we propose a novel approach of hybrid feature extraction and hierarchical classification to recognize the glyphs of offline handwritten Telugu characters. In the proposed method, hybrid features are extracted from the glyphs and the glyphs are recognized using a hierarchical classification system. The hybrid features are extracted on the basis of glyph dimensions, positions of small glyphs, and zone-wise features for glyph classification. We implemented a two-level hierarchical classification method for classifying the glyphs of offline handwritten Telugu characters. The proposed method efficiently recognizes the glyphs of offline handwritten Telugu characters. The overall recognition rate is 88.15%. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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