Computational intelligent color normalization for wheat plant images to support precision farming

Susanto B. Sulistyo, W. L. Woo, S. S. Dlay

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Image 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.

Original languageEnglish
Title of host publicationProceedings of the 8th International Conference on Advanced Computational Intelligence, ICACI 2016
PublisherIEEE
Pages130-135
Number of pages6
ISBN (Electronic)9781467377829
ISBN (Print)9781467377805
DOIs
Publication statusPublished - 11 Apr 2016
Event8th International Conference on Advanced Computational Intelligence, ICACI 2016 - Chiang Mai, Thailand
Duration: 14 Feb 201616 Feb 2016

Conference

Conference8th International Conference on Advanced Computational Intelligence, ICACI 2016
CountryThailand
CityChiang Mai
Period14/02/1616/02/16

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