This paper describes a novel stereovision matching approach based on omni-directional images obtained with fish-eye lenses in forest environments. The goal is to obtain a disparity map as a previous step for determining the volume of wood in the imaged area. The interest is focused on the trunks of the trees, due to the irregular distribution of the trunks; the most suitable features are the pixels. A set of six attributes is used for establishing the matching between the pixels in both images of the stereo pair. The final decision about the matched pixel is taken based on the Choquet Fuzzy Integral paradigm, which is a technique well tested for combining classifiers. The use and adjusting of this decision approach to our specific stereo vision matching problem makes the main finding of the paper. The procedure is based on the application of three well known matching constraints. The proposed approach is compared favourably against the usage of simple features and other fuzzy strategy that combines the simple ones.