Segmentation and size estimation of tomatoes from sequences of paired images
In this paper, we present a complete system to monitor the growth of tomatoes from images acquired in open fields. This is a challenging task because of the severe occlusion and poor contrast in the images. We approximate the tomatoes by spheres in the 3D space, hence by ellipses in the image space. The tomatoes are first identified in the images using a segmentation procedure. Then, the size of the tomatoes is measured from the obtained segmentation and camera parameters. The shape information combined with temporal information, given the limited evolution from an image to the next one, is used throughout the system to increase the robustness with respect to occlusion and poor contrast.
image segmentation parametric active contours shape constraint precision farming metric measurement