Recognition of handwritten digits by image processing methods and classification models
OCR (Optical Character Recognition) is a line of research within image processing for which many techniques and methodologies have been developed. Set of pixels recognized based on the digitalized image and this study presents an iterative process that consists of five phases of the OCR. For this pu...
- Autores:
-
amelec, viloria
Rico, Reinaldo
Pineda, Omar
- Tipo de recurso:
- http://purl.org/coar/resource_type/c_816b
- Fecha de publicación:
- 2020
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/7271
- Acceso en línea:
- https://hdl.handle.net/11323/7271
https://repositorio.cuc.edu.co/
- Palabra clave:
- Classification models
Genetic algorithm
Image processing
Methods
Recognition of handwritten digits
- Rights
- closedAccess
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International
| Summary: | OCR (Optical Character Recognition) is a line of research within image processing for which many techniques and methodologies have been developed. Set of pixels recognized based on the digitalized image and this study presents an iterative process that consists of five phases of the OCR. For this purpose, several image processing methods are applied, as well as two variable selection methods, and several supervised automated learning methods are explored. Among the classification models, those of deep learning stand out for their novelty and enormous potential. |
|---|