Assessment of crops by outdoor computer vision / Afgrødevurdering og udendørs computer vision

Visual information of crops has for centuries been used by mankind for assessment of the growth condition of crops. By visual information the spatial distribution of reflection from the canopy is used for detection of specific patterns related to lack of nutrients or infestation by diseases, i.e. lack of manganese will turn out as light brown spots on the leaves whereas lack of calcium will turn out as miscolouring of leaves from the leaf edge and inwards. So far, development of sensors for detection of plant nutrient deficiency has been oriented towards nitrogen and with sensor types that do not take the spatial pattern of the reflection into account. The objective of this project is to develop computer vision methods that may enable a more detailed analysis of the reflection from canopies by: 1) identification of areas without specular reflection and 2) correct images for uneven illumination conditions. In this way a reliable quantitative analysis of the canopy may be obtained for optimal growth control. The project was concluded with a report early 2003 providing the following major contributions: - A pioneering investigation of computer vision analysis of outdoor scenes with high dynamic range of intensities - 3D reconstruction and description of plants for detection of reflection patterns - Modelling of "Red Edge Inflection Point" using the Wiebull function for accurate estimation of the "clorofyl" content and its distribution across the leaf segments The two first studies have given promising results and international publications. All results will be followed up in the ACROSS project. Funded by The Danish Agricultural and Veterinary Research Council, February 2002-March 2003. (Hans J. Andersen)