Fuzzy c-means based plant segmentation with distance dependent threshold

An important element in weed control using machine vision is the ability to identify plant species based on shape. For this to be done, it is often necessary to segment the plants from the soil. This may cause problems, if the colour of a plant is not consistent, since plants are then at risk of being separated into several objects. This study presents a plant segmentation method based on fuzzy c-means and a distance transform. This segmentation method is compared with four other plant segmentation methods based on various parameters, including the ability to maintain the plants as whole, connected components. The method presented here is found to be better at preserving plants as connected objects, while keeping the false positive rate low compared to commonly used segmentations techniques.