Checking automobile fuel adulteration using image processing techniques

This paper tries to characterize different samples of automobile fuel, petrol contaminated with different proportions of kerosene, and thereby proposing a sensor for checking adulteration of fuel using image processing techniques. Images of different samples are captured using a camera and image processing is employed to extract the trends of measures of texture analysis. The findings show that adulterating fuel with different proportions of impurities display varying characteristics of five measures of texture. This research is enormously significant to the development of sensors to detect fuel adulteration.