Abstract: A video based method to detect volatile organic compounds (VOC) leaking out of components used in chemical processes in petrochemical refineries. Leaking VOC plume from a damaged component has distinctive properties that can be detected in realtime by an analysis of images from a combination of infrared and optical cameras. Particular VOC vapors have unique absorption bands, which allow these vapors to be detected and distinguished. A method of comparative analysis of images from a suitable combination of cameras, each covering a range in the IR or visible spectrum, is described. VOC vapors also cause the edges present in image frames to loose their sharpness, leading to a decrease in the high frequency content of the image. Analysis of image sequence frequency data from visible and infrared cameras enable detection of VOC plumes. Analysis techniques using adaptive background subtraction, sub-band analysis, threshold adaptation, and Markov modeling are described.