An adaptive technique for color image segmentation is presented in this paper. The segmentation is performed using a multiresolution scheme and considering the background areas have quite uniform color features at a low-resolution representation of the image. First, a pyramidal representation of the original image is built. Then segmentation is improved iteratively at each resolution using color information. This method allows to extract background areas in outdoor images. Background and foreground separation is especially useful in initialization of object tracking applications. Several color spaces are compared in order to determine a robust method specially with respect to illumination changes which frequently occur in outdoor images. Mean value of Hue component from HSV (Hue, Saturation, Value) color space is selected as the best decision criterion for image matching. Segmentation results of color image from soccer game video sequences are presented to illustrate the method efficiency.