Human face detection is the first step for a fully automated face recognition system. It is also crucial to video surveillance systems, human computer interface, image/video retrieval systems. We consider color a very useful cue for face detection in color images. So that we propose a fast skin color detector for detecting in skin color patches in images with complex illumination and background. The accuracy and performance of this detector will have great affect on the upcoming feature extraction and verification processing. In our architecture, after applying a novel adaptive lighting compensation to alleviate the correct the illumination, a skin color filter based on normalized RGB color space is used to detect skin tone patches. Then, in order to remove noises and increase accuracy, morphological operations are used to refine the mask generated by the filter. Finally, the refined mask is used to gain the final result. For each step, including lighting compensation, color space modeling and final results, when compared to existing skin-tone color filtering algorithms, our algorithm is proven to be more robust and efficient by algorithm analysis and experiments results. After the processing, data amount is dramatically reduced and later algorithms can start with the skin patches remained.