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All Journal International Journal of Electrical and Computer Engineering
Keun Ha Choi
Artificial Intelligent R&D Center
Computer Science & IT Electrical & Electronics Engineering

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Illumination-invariant vegetation detection for a vision sensor-based agricultural applications Keun Ha Choi; SooHyun Kim
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i2.pp1284-1292

Abstract

In this paper, we propose a novel method, illumination-invariant vegetation detection (IVD), to improve many aspects of agriculture for vision-based autonomous machines or robots. The proposed method derives new color feature functions from simultaneously modeling the spectral properties of the color camera and scene illumination. An experiment in which an image sample dataset was acquired under nature illumination, including various intensities, weather conditions, shadows and reflections, was performed. The results show that the proposed method (IVD) yields the highest performance with the lowest error and standard deviation and is superior to six typical methods. Our method has multiple strengths, including computational simplicity and uniformly high-accuracy image segmentation.
Co-Authors SooHyun Kim