Classifying Airborne Particles

Considering the selective Rayleigh light scattering behaviour by small particles, this study adopts a new technique to classify nano-scale airborne particles with colour histogram features. Noise was generated using scattered light by five different sized particles with a continuous spectrum of light. Each video frame was divided into its red, green and blue planes and noise was isolated using a modified frame difference method. The mean and standard deviation of the maximum value index of intensity histograms over a predefined number of frames were used to classify the type of particles. Results show that the classifier was able to distinguish the four types of particles, polyurethane smoke, kerosene smoke, water steam and cooking oil smoke, with a 100% accuracy.