Affiliations: ENSAR, Laboratoire Informatique, Rennes, France | USARQ‐INRA, Rennes, France | IRISA, AÏDA project, Rennes, France E‐mail: {clargoue,cordier}@irisa.fr
Note: [] Corresponding author: Christine Largouët, Laboratoire informatique ENSAR, 65 rue de St Brieuc, 35042 Rennes Cedex, France.
Abstract: This paper deals with the integration of domain knowledge to improve the landcover classification of a sequence of images. This new approach consists in representing the plot of land as a dynamic system and in modelling its evolution (knowledge about crop cycles, rotations and farmer practices) with the timed automata formalism. The main feature of this work is to improve the classification provided by a traditional classification with data resulting from the simulation of the plot evolution model. The aim of this paper is to focus on the experiments carried out on a sequence of five images. The problem of classification refinement and the model used to capture domain knowledge are first presented. The emphasis is then put on the results and their interpretation that show the contribution of the method to improve the classification of images.
