Skip to Main content Skip to Navigation
Conference papers

A Detection Method of Rice Process Quality Based on the Color and BP Neural Network

Abstract : This paper proposed a detection method of rice process quality using the color and BP neural network. A rice process quality detection device based on computer vision technology was designed to get rice image, a circle of the radius R in the abdomen of the rice was determined as a color feature extraction area, and which was divided into five concentric sub-domains by the average area, the average color of each sub-region H was extraction as the color feature values described in the surface process quality of rice, and then the 5 color feature values as input values were imported to the BP neural network to detection the surface process quality of rice. The results show that the average accuracy of this method is 92.50% when it was used to detect 4 types of rice of different process quality.
Document type :
Conference papers
Complete list of metadata

Cited literature [10 references]  Display  Hide  Download
Contributor : Hal Ifip Connect in order to contact the contributor
Submitted on : Monday, July 10, 2017 - 5:28:50 PM
Last modification on : Tuesday, April 5, 2022 - 9:02:02 PM
Long-term archiving on: : Wednesday, January 24, 2018 - 5:36:53 PM


Files produced by the author(s)


Distributed under a Creative Commons Attribution 4.0 International License



Peng Wan, Changjiang Long, Xiaomao Huang. A Detection Method of Rice Process Quality Based on the Color and BP Neural Network. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. pp.25-34, ⟨10.1007/978-3-642-18333-1_4⟩. ⟨hal-01559632⟩



Record views


Files downloads