Besides harvesting the fruits, a very time demanding task is removing old leaves from cucumber and tomato plants grown in greenhouses. To be able to automate this process by a robot, a leaf detection method is required. One possibility for the detection is to exploit the different dynamic behaviour of leaves and stems in case they are excited by mechanical impulse such as an airstream. The objective of this paper is to investigate this technique using a camera and image analysis. For the experiments carried out, images of a tomato crop were used. Images were taken with a digital camera from different distances. To generate an air stream, different radial blowers were used. A sequence of 5 digital images was recorded with a sample rate of 1 second with different settings. To find the differences between the images, the intensity of the images were mathematically subtracted. The resulting binary images were further processed with the aim to extract the leaf positions. These steps included automatic thresh-holding, noise reduction and morphological image analysis operations. It was found that moving objects in the images could be detected using the method described above. Budging objects could only successfully be traced if colour, intensity or structure of the moving object differed with the colour, intensity or structure of the background. The blowing direction had a strong influence on the movements. It is concluded that with this technique not only leaves can be detected but also other parts as e.g. fruits, stems and branches can be discriminated. Already many years ago research was focused on robotics in horticultural crop production (e.g. Tillett, 1993; Edan, 1995). The reduction of labour costs, problems with the availability of skilled labour and the improvement of the production process both quantitatively as well as qualitatively were the main driving forces for research on the development of an autonomous harvesting robot for cucumber in greenhouses at Agrotechnology & Food Innovations, formerly known as IMAG B.V. (Van Henten et al., 2002, 2003. Many of the robotic applications require locating the position of a special part of the plant, often vision systems are used for this purpose. McFarlane (1993) reported a system to detect segments of microplants, Yang (1993) and Wolfe and Sandler (1985) worked on a stem detection algorithm for different fruit. Meuleman et al. (2000) developed a cucumber fruit detection system. With vegetables, next to harvesting a very time demanding task is removing old leaves from the plants. This task has not only to be done for cucumbers but also for tomatoes, which are grown using a high wire cultivation system in Dutch greenhouses. To be able to automate this process by a robot, a leaf detection method is required. One possibility for the detection could be to exploit the different dynamic behaviour of leaves and stems when excited by a mechanical impulse, such as induced by an air stream. One may expect that leaves will show a stronger motion than stems and fruit. Analysing the differences in several images of the same scene should give the possibility of extracting the leaf positions. The objective of this paper is to investigate this technique. As far as the authors are aware, the use of motion analysis for plant detection has not been described in literature before.
Hemming et al. REF use a sequence of images and leaf movement to segment the leaves and an automatic thresholding to obtain individual leaf position.