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Real-time Detection of Between-row Weeds Using Machine Vision

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Paper number  031004,  2003 ASAE Annual Meeting . (doi: 10.13031/2013.15381)
Authors:   Wenhua Mao, Yiming Wang, Yueqing Wang
Keywords:   Machine vision, Image processing, Real-time detection, Between-row weed

A system used machine vision to detect between-row weeds was developed and tested in laboratory with outdoor lighting conditions. A software system named Between-row Weeds Detection System was developed to process the images. The proposed algorithms used color information to discriminate between plants and background, whilst novel analysis techniques were applied to distinguish between crop and between-row weeds by use of the information of plants location within the field. Firstly, the excessive green algorithm was adopted to gray the source images. Secondly, the gray-level image was transformed to binary image by use of the algorithm of the maximum variance optimal threshold selection. Finally, crops and weed were segmented by use of the seed-fill algorithm. It was indicated that the DWB system had the superiority in real-time.

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