DocumentCode
2963068
Title
Using Neural Network to Model the Relationship between Plant Surface Color and its Pigment
Author
Qingmao, Zeng ; Tong, Zhang ; Tonglin, Zhu
Author_Institution
Instn. of Agric. Multimedia Technol., South China Agric. Univ., Guangzhou, China
Volume
2
fYear
2011
fDate
28-29 March 2011
Firstpage
303
Lastpage
307
Abstract
Combining the intelligent algorithm such as BP neural network and support vector maching (SVM) with traditional chemical method, this paper models the relationship between plant surface color and its pigment. Using the neural network model constructed above, people can figure out the content of plant pigments by getting the corresponding plant surface color information. Compared with the traditional modeling methods, this method can significantly save time and experimental supplies. Furthermore, it is easy to implement because it needn´t touch samples and doesn´t cause any damage to samples. So this method provides a practical tool for non-destructive measurements of plant pigments and solutions to explore the mystery of plant color.
Keywords
agricultural products; agriculture; backpropagation; image colour analysis; neural nets; support vector machines; BP neural network model; Chinese kale stems; chemical method; plant pigments; plant surface color; support vector maching; Artificial neural networks; Data models; Image color analysis; Machine vision; Pigments; Support vector machines; Training; BP neural network; Chinese kale stems; HSV mean; Support vector machine (SVM); plant pigment;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Computation Technology and Automation (ICICTA), 2011 International Conference on
Conference_Location
Shenzhen, Guangdong
Print_ISBN
978-1-61284-289-9
Type
conf
DOI
10.1109/ICICTA.2011.361
Filename
5750886
Link To Document