Computer vision system in real-time for color determination on flat surface food
Descripción del Articulo
Artificial vision systems also known as computer vision are potent quality inspection tools, which can be applied in pattern recognition for fruits and vegetables analysis. The aim of this research was to design, implement and calibrate a new computer vision system (CVS) in real-time for the color m...
Autores: | , , , , , |
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Formato: | artículo |
Fecha de Publicación: | 2013 |
Institución: | Universidad Nacional de Trujillo |
Repositorio: | Revistas - Universidad Nacional de Trujillo |
Lenguaje: | inglés |
OAI Identifier: | oai:ojs.revistas.unitru.edu.pe:article/98 |
Enlace del recurso: | https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/98 |
Nivel de acceso: | acceso abierto |
Materia: | Computer Vision RGB model CIELab model food quality control Matlab |
Sumario: | Artificial vision systems also known as computer vision are potent quality inspection tools, which can be applied in pattern recognition for fruits and vegetables analysis. The aim of this research was to design, implement and calibrate a new computer vision system (CVS) in real-time for the color measurement on flat surface food. For this purpose was designed and implemented a device capable of performing this task (software and hardware), which consisted of two phases: a) image acquisition and b) image processing and analysis. Both the algorithm and the graphical interface (GUI) were developed in Matlab. The CVS calibration was performed using a conventional colorimeter (Model CIEL* a* b*), where were estimated the errors of the color parameters: eL* = 5.001%, and ea* = 2.287%, and eb* = 4.314 % which ensure adequate and efficient automation application in industrial processes in the quality control in the food industry sector. |
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).