Segmentation of Foreground Row Trees in Apple Orchard Images Collected by Ground Vehicles

Abstract

This paper proposes a fully automatic method for the segmentation of foreground row trees in industrial apple orchard images. The segmentation is based on analyzing a combination of a depth map constructed by the Marigold diffusion model and a model depth map created using automatically detected vanishing lines. The output of the method is a binary mask of the selected foreground trees. These masks can be used in subsequent stages of the image processing pipeline to discard false detections in the fruit counting module. The proposed method was evaluated as a preprocessing step for an apple detection method using the OrchardAppleDet- MSU dataset. Experiments showed that the proposed method can improve the quality of apple detection by 1–3%.