Ripeness determination in feijoa fruits by using a computer vision system and colour. information

Determine the ripeness of agricultural products generally depends on an analysis by human experts. The final decision on the state of maturity where the product is found, requires correlating some of their physical features with chemical and internal characteristics of the fruit. The need to preserve the integrity of the fruit on this analysis requires implementation of technologies to pass judgment on its condition without destroying it. The use of colour index, as physical property, contributes to solving this problem. In this document is presented a machine vision system to classify into three stages of maturity a specific exotic fruit: feijoa -Acca sellowiana-. The obtained classification using artificial intelligence tools, as these are artificial neural networks, have shown an adequate classification over 90% from 156 images of Feijoa fruit used in the study.

• Tipo de recurso: http://purl.org/coar/resource_type/c_6516
• Fecha de publicación: 2016
• Institución: Universidad Pedagógica y Tecnológica de Colombia
• Repositorio: RiUPTC: Repositorio Institucional UPTC
• Idioma: spa
• OAI Identifier: oai:repositorio.uptc.edu.co:001/10232
• Acceso en línea: https://revistas.uptc.edu.co/index.php/investigacion_duitama/article/view/5603; https://repositorio.uptc.edu.co/handle/001/10232
• Palabra clave: Acca sellowiana; feijoa; pattern recognition; computer vision system.; Acca sellowiana; feijoa; reconocimiento de patrones; sistema de visión por computador.
• License: Derechos de autor 2016 REVISTA DE INVESTIGACIÓN, DESARROLLO E INNOVACIÓN