Desarrollo de un clasificador de aceitunas de mesa por su variedad.
Fecha
2020-03-06
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Universidad de Guayaquil. Facultad de Ciencias Matemáticas y Físicas. Carrera de Ingeniería en Sistemas Computacionales.
Resumen
El consumo de aceitunas se ha incrementado debido a su utilización en el área de la gastronomía, el éxito de su producción se origina en países europeos como; España, Italia, Francia, entre otros, extendiéndose a países latinoamericanos como Argentina y Uruguay. Existe una amplia variedad de aceitunas, siendo el sujeto de estudio de esta investigación las aceitunas de mesa las cuales son verdes, cambiantes y negras, su calidad depende del nivel de madurez al momento de su recolección. Ante tal situación, el presente trabajo tiene como objetivo el desarrollo de un clasificador de aceitunas de mesa por su variedad mediante la metodología del procesamiento digital de imágenes que considera un conjunto de técnicas de coloración, grises, pixeles, entre otros, tomando en cuenta las características importantes del fruto como el color, la forma y textura, las mismas que se obtienen mediante redes neuronales convolucionales, el cual generará un modelo que permitirá detectar las aceitunas mediante la webcam, captando aquellas que se encuentren en óptimas condiciones para ser procesadas ofrezcan una mejor calidad en la preparación de platos gourmet.
The consumption of olives has increased due to its use in the area of gastronomy, the success of its production originates in European countries such as; Spain, Italy, France, among others, extending to Latin American countries such as Argentina and Uruguay. There is a wide variety of olives, being the subject of this research the table olives which are green, changing and black, their quality depends on the level of maturity at the time of collection. Given this situation, the present work aims to develop a table olives sorter by its variety through the methodology of digital image processing that considers a set of coloring techniques, gray, pixels, among others, taking into account the characteristics important fruit such as color, shape and texture, the same that are obtained through convolutional neural networks, which will generate a model that will detect the olives through the webcam, capturing those that are in optimal conditions to be processed offer a better quality in the preparation of gourmet dishes.
The consumption of olives has increased due to its use in the area of gastronomy, the success of its production originates in European countries such as; Spain, Italy, France, among others, extending to Latin American countries such as Argentina and Uruguay. There is a wide variety of olives, being the subject of this research the table olives which are green, changing and black, their quality depends on the level of maturity at the time of collection. Given this situation, the present work aims to develop a table olives sorter by its variety through the methodology of digital image processing that considers a set of coloring techniques, gray, pixels, among others, taking into account the characteristics important fruit such as color, shape and texture, the same that are obtained through convolutional neural networks, which will generate a model that will detect the olives through the webcam, capturing those that are in optimal conditions to be processed offer a better quality in the preparation of gourmet dishes.
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Extracción de Características, Procesamiento digital de Imágenes, Reconocimiento de Patrones, Segmentación de Imágenes, Sistema de Visión Artificial, Artificial Vision System, Digital Image Processing, Feature Extraction, Image Segmentation, Pattern Recognition