Los estudiantes Luisa María Medina Barragán, Miguel José Delgado Gutiérrez, Daniel Felipe Herrera Guillén y la docente Jennifer Paola Corredor Gómez del Semillero en Agricultura de Precisión, Grupo de Investigación Innovatic, presentaron en el International Week of Research, Development and Innovation la ponencia que se describe posteriormente.
PONENCIA. Machine Vision Identifier Of Healthy Strawberries.
RESEÑA. In recent years, the price of strawberries in Colombia has fallen, which has generated a greater demand from consumers and has brought benefits to the producers, making their business more profitable. For this reason, producers are getting interested to enter in the international trade, making it necessary to consider the minimum export requirements to fulfil the product quality. In order to make an improvement in the selection process and considering the four basic parameters determined by NTC 4103 (Health, Form, Maturity and Size). We propose an algorithm to classify strawberries, taking into account the international «Standard for Quick Frozen Strawberries»(CODEX STAN 62-1981) that defines the quality parameters of the strawberry. The project was developed using the mathematical software tool MATLAB to determine the quality of strawberries with image processing and to design an user interface for its use. The software has a reliability of 80% when determining the quality of the strawberry, with an estimated processing time of 3 seconds per photo.
Keywords. Strawberry, Quality Product, Selection Process, MATLAB, Image Processing.
PhD. Jennifer Paola Corredor Gómez