MOMENTOS DE LOS LÍMITES GEOMÉTRICOS Y SU APLICACIÓN AL CONTROL DE CALIDAD AUTOMATIZADO EN LA INDUSTRIA
In this research the performance of the Chen's Improved (Boundary) Moments is carefully compared to that of the traditional (Massive) Moments. To achieve this investigation, the pattern recognition power of the former is thoroughly assessed against that of the latter. The boundary moments are e...
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2006 |
| País: | Perú |
| Institución: | Universidad Nacional Mayor de San Marcos |
| Repositorio: | Revistas - Universidad Nacional Mayor de San Marcos |
| Idioma: | español |
| OAI Identifier: | oai:revistasinvestigacion.unmsm.edu.pe:article/5759 |
| Acceso en línea: | https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/5759 |
| Access Level: | acceso abierto |
| Palabra clave: | Artificial intelligence cybernetic vision pattern recognition. Inteligencia artificial visión cibernética reconocimiento del modelo. |
| Sumario: | In this research the performance of the Chen's Improved (Boundary) Moments is carefully compared to that of the traditional (Massive) Moments. To achieve this investigation, the pattern recognition power of the former is thoroughly assessed against that of the latter. The boundary moments are evaluated by two methods, in the first by edge-tracing, in the second method the edge pixels are considered as though they are met when sweeping the image space. It is concluded that the computation of the Boundary Moments by sweeping the image space associates minimum computational complexity to a high enough object classification efficiency, thus they may be used in lieu of the traditional moments. |
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