Fractal dimension and lacunarity are two fractal measures widely used for image analysis, segmentation and indexation. In this paper, we show how these two fractal features are able to capture several aspects that characterize the degradation of the video signal, based on the fact that the quality perceived is directly proportional to the fractal complexity of an image. Thus, we demonstrate that the fractal dimension and lacunarity can be used to objectively assess the quality of the video signal and how they can be used as metrics for the user-perceived video quality degradation for an MPEG-4 streaming application. Unfortunately, all the existing approaches are defined only for binary and greyscale images. Based on the probabilistic algorithm for the estimation of the fractal dimension and computation of lacunarity, we propose a colour approach that makes possible the analysis of the complexity in the RGB colour space of any colour image. We discuss our experimental results and then draw the conclusions.