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Reduced-Dimension Clustering For Vegetation Segmentation, Brian L. Steward, Lei F. Tian, Dan Nettleton, Lie Tang
Reduced-Dimension Clustering For Vegetation Segmentation, Brian L. Steward, Lei F. Tian, Dan Nettleton, Lie Tang
Dan Nettleton
Segmentation of vegetation is a critical step in using machine vision for field automation tasks. A new method called reduced-dimension clustering (RDC) was developed based on theoretical considerations about the color distribution of field images. RDC performed unsupervised classification of pixels in field images into vegetation and background classes. Bayes classifiers were then trained and used for vegetation segmentation. The performance of the classifiers trained using the RDC method was compared with that of other segmentation methods. The RDC method produced segmentation performance that was consistently high, with average segmentation success rates of 89.6% and 91.9% across both cloudy and …