Study of Segmentation Techniques for Cursive English Handwriting Recognition
| Autor: | Reena Kharat, Pritam S. Dhande |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
business.industry
Computer science Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Optical character recognition computer.software_genre Field (computer science) ComputingMethodologies_PATTERNRECOGNITION Handwriting recognition Handwriting ComputingMethodologies_DOCUMENTANDTEXTPROCESSING Segmentation Artificial intelligence business computer Cursive Character recognition Natural language processing |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9789811055195 |
| DOI: | 10.1007/978-981-10-5520-1_51 |
| Popis: | This paper aims to present a study of different segmentation techniques for optical character recognition of handwritten cursive English script. Optical character recognition is a very challenging research field. There are scanners with inbuilt OCR for printed documents but not for handwritten documents. Character recognition of handwritten cursive English script is a very challenging task. In cursive English handwriting, the characters in a word are connected to each other. So the segmentation and feature extraction of cursive English script are much difficult. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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