Adaptive color image processing and recognition for varying backgrounds and illumination conditions

The paper presents a fuzzy-based method for recognizing color objects in a complex background under varying illumination. Fuzzy rules are generated using a fuzzy associative memory (FAM) training method to cope with chromatic distortion. The color model used is the hue, saturation, and value (HSV) color model. The authors propose a unique adaptive fuzzy system, motivated by the human vision system's color constancy, in order to accommodate varying background color and illumination conditions, as well as incorrect focus of the camera. This adaptive system can adjust the fuzzy rules dynamically based on the properties of surrounding pixels in order to make a decision. The proposed method is tested on a two-hour video tape captured by a GPSVan, in which real-world scenes may have incorrect video camera focus, color distortions, and varying illumination conditions. Experimental results are reported and analyzed.