What is the optimal stitching orientation from an aerial survey perspective?

Mosaicing is a technique that allows obtaining a large high resolution image by stitching several images together. These base images are usually acquired from an elevated point of view. Until recently, low-altitude image acquisition has been performed typically by using using airplanes, as well as other manned platforms. However, mini unmanned aerial vehicles (MUAV) endowed with a camera have lately made this task more available for small for cicil applications, for example for small farmers in order to obtain accurate agronomic information about their crop fields. The stitching orientation, or the image acquisition orientation usually coincides with the aircraft heading assuming a downwards orientation of the camera. In this paper, the efect of the image orientation in the eficiency of the aerial coverage path planning is studied. Moreover, an algorithm to compute an optimal stitching orientation angle is proposed and results are numerically compared with classical approaches.

An image segmentation based on a genetic algorithm for determining soil coverage by crop residues

Determination of the soil coverage by crop residues after ploughing is a fundamental element of Conservation Agriculture. This paper presents the application of genetic algorithms employed during the fine tuning of the segmentation process of a digital image with the aim of automatically quantifying the residue coverage. In other words, the objective is to achieve a segmentation that would permit the discrimination of the texture of the residue so that the output of the segmentation process is a binary image in which residue zones are isolated from the rest. The RGB images used come from a sample of images in which sections of terrain were photographed with a conventional camera positioned in zenith orientation atop a tripod. The images were taken outdoors under uncontrolled lighting conditions. Up to 92% similarity was achieved between the images obtained by the segmentation process proposed in this paper and the templates made by an elaborate manual tracing process. In addition to the proposed segmentation procedure and the fine tuning procedure that was developed, a global quantification of the soil coverage by residues for the sampled area was achieved that differed by only 0.85% from the quantification obtained using template images. Moreover, the proposed method does not depend on the type of residue present in the image. The study was conducted at the experimental farm “El Encín” in Alcalá de Henares (Madrid, Spain).