Data/hora: 12/06/2024 05:48:56

Provedor de dados: | 65
País: | Brazil
Título: | Mature pomegranate recognition methods in natural environments using machine vision
Autores: | Lei,Xiangxiao; Ouyang,Honglin; Xu,Lijuan.
Data: | 2019-01-01
Ano: | 2019
Palavras-chave: | Punica granatum L.; Machine vision; Fuzzy clustering; Kernel; Image segmentation.
Resumo: | ABSTRACT:  The use of machine vision to recognize mature pomegranates in natural environments is of major significance in improving the applicability and work efficiency of picking robots. By analyzing the color characteristics of color images of mature pomegranates under different illumination conditions, the feasibility of the YCbCr color model for pomegranate image recognition under different illumination conditions was proven. First, the Cr component map of pomegranate image is selected and then the pomegranate fruit is segmented by the kernel fuzzy C-means clustering algorithm to obtain the pomegranate image. Contrast experiments of pomegranate image segmentation under different illumination conditions were then performed using the proposed kernel fuzzy C-means clustering algorithm, the fuzzy C-means clustering algorithm, the Otsu algorithm and the threshold segmentation algorithm. Results of the experiments verified the effectiveness and superiority of the proposed algorithm.
Tipo: | Info:eu-repo/semantics/article
Idioma: | Inglês
Identificador: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782019000900351
Editor: | Universidade Federal de Santa Maria
Relação: | 10.1590/0103-8478cr20190298
Formato: | text/html
Fonte: | Ciência Rural  v.49 n.9 2019
Fonte: | info:eu-repo/semantics/openAccess