This paper presents a method for direct smoke detection from video without enhancement pre-processing steps. Smoke is characterized by transparency, gray color and irregularities in motion, which are hard to describe with the basic image features. A method for robust smoke description using a color balancing algorithm and turbulence calculation is presented in this work. Background extraction is used as a first step in processing. All moving objects are candidates for smoke. We make use of Gray World algorithm and compare the results with the original video sequence in order to extract image features within some particular gray scale interval. As a last step we calculate shape complexity of turbulent phenomena and apply it to the incoming video stream. As a result we extract only smoke from the video. Features such shadows, illumination changes and people will not be mistaken for smoke by the algorithm. This method gives an early indication of smoke in the observed scene.