Fuzzy Integral for Moving Object Detection

Fida El Baf (1) , Thierry Bouwmans (1) , Bertrand Vachon (1)

1 MIA - Mathématiques, Image et Applications - EA 3165

Detection of moving objects is the first step in many applications using video sequences like video-surveillance, optical motion capture and multimedia application. The process mainly used is the background subtraction which one key step is the foreground detection. The goal is to classify pixels of the current image as foreground or background. Some critical situations as shadows, illumination variations can occur in the scene and generate a false classification of image pixels. To deal with the uncertainty in the classification issue, we propose to use the Choquet integral as aggregation operator. Experiments on different data sets in video surveillance have shown a robustness of the proposed method against some critical situations when fusing color and texture features. Different color spaces have been tested to improve the insensitivity of the detection to the illumination changes. Then, the algorithm has been compared with another fuzzy approach based on the Sugeno integral and has proved its robustness.

Mots clés: Foreground Detection; Fuzzy Integral; Moving Object Detection

Domaines: Traitement des images [eess.IV]

Fida El Baf, Thierry Bouwmans, Bertrand Vachon. Fuzzy Integral for Moving Object Detection. FUZZ-IEEE 2008, Jun 2008, Hong-Kong, Hong Kong SAR China. pp.1729-1736, ⟨10.1109/FUZZY.2008.4630604⟩. ⟨hal-00333086⟩