In this work, we propose a robust classification system that estimates the advertising panels visibility in real time. For each frame of the sequence, a set of descriptors is extracted to characterize a specific part of the scene: the grass field. Gathering all these descriptors, a decision tree determines whether the LED panels are visible in that frame. In order to improve the robustness of the algorithm, the redundancy of the temporal domain is exploited. The validity of the proposed algorithm has been tested on a large amount of frames representing 250 minutes of broadcasted football sequences in a wide variety of scenarios. Promising results have been obtained with a 95% of accuracy in the classification of these images.