Ultimate leveling based on Mumford-Shah energy functional applied to plant detection

Abstract

This paper presents a filter based on energy functions applied to the ultimate levelings which are powerful image operators based on numerical residues. Within a multi-scale framework, these operators analyze a given image under a series of levelings. Thus, contrasted objects can be detected if a relevant residue is generated when they are filtered out by one of these levelings. During the residual extraction process, it is very common that undesirable regions of the input image contain residual information that should be filtered out. These undesirable residual regions often include desirable residual regions due to the design of the ultimate levelings which consider maximum residues. In this paper, we improve the residual information by filtering out residues extracted from undesirable regions. In order to test our approach, some experiments were conducted in plant dataset and the results show the robustness of our approach.