期刊名称：Advance Journal of Food Science and Technology
印刷版ISSN：2042-4868
电子版ISSN：2042-4876
出版年度：2013
卷号：5
期号：04
页码：482-487
出版社：MAXWELL Science Publication
摘要：In order to prevent artificial ripening tomato into markets to harm consumers' health, a double parallel genetic neural network identification system was designed. This system obtained tomato external color characteristic parameters (R, G, B) through the computer vision device and changed the RGB value into HIS value. Put tomato external color characteristic parameters as input, tomato maturity properties as output and verified the system with test samples. The test results show that, the correct recognition rate of the system is 93.8%, providing the reference for further research of artificial ripening tomato and natural mature tomato.
