In this paper a fuzzy statistical color–based approach for semantic characterization of animation movies is proposed. Color is a major feature of animation movies: each movie has its own color distribution. Deriving semantic information about the used color artistry concepts or about the sensation induced by the movie's color distribution should be an ideal analysis-tool for the animation experts. First, the movie is divided into shots and a movie abstract is then automatically generated. Color reduction is applied on each retained frame using an error diffusion algorithm with a predefined color palette. Then, a global weighted color histogram of the movie is computed by taking into account each shot relevance. It serves as a basis of computation for relevant color-based statistics, such as the elementary colors distribution or the light/dark color ratios. Using a fuzzy representation, meaningful color–based semantic information is then derived from the obtained parameters, namely: light–dark contrast, cold-warm contrast and contrast of saturation schemes, the color variations/diversity and the adjacent/complementary colors. The proposed approach was tested on several animation movies.