Computational Intelligent Color Normalization for Wheat Plant Images to Support Precision Farming

Publons ID(not set)
Wos IDWOS:000381807500023
Doi
TitleComputational Intelligent Color Normalization for Wheat Plant Images to Support Precision Farming
First Author
Last Author
AuthorsSulistyo, SB; Woo, WL; Dlay, SS;
Publish Date2016
Journal Name2016 EIGHTH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI)
Citation2
AbstractImage colors are considerably affected by the intensity of the light source. In this paper, we propose a color constancy method using neural networks fusion to normalize images captured under sunlight with a variation of light intensities. A genetic algorithm is also applied to optimize the color normalization. A 24-patch Macbeth color checker is utilized as the reference to normalize the images. The results of our proposed method is superior to other methods, i.e. the conventional gray world and scale-by-max methods, as well as linear model and single neural network method. Furthermore, the proposed method can be used to normalize wheat plant images captured under various light intensities.
Publish TypeBook
Publish Year2016
Page Begin130
Page End135
Issn
Eissn
Urlhttps://www.webofscience.com/wos/woscc/full-record/WOS:000381807500023
AuthorSUSANTO BUDI SULISTYO, S.TP, M.Si, PhD
File111456.pdf