Real-time Image Intensification in Tobacco Sorting System Under Low Illumination

The foreign matter rejecting performance of a tobacco sorting system decreases with the attenuation of illumination, therefore the function of image intensification was incorporated on the basis of optimized Gauss homomorphic filtering algorithm. The image of tobacco leaf under low illumination was converted swiftly from its RGB (Red-Green-Blue) space into an HSV (Hue-Saturation-Value) space in order to separate color from luminance, and the luminance component V was intensified by a real-time spatial homomorphic filter, then stretched by an introduced adaptive coefficient, finally HSV was converted into RGB. The results showed that this method could effectively correct the color, contrast and luminance of an image under low illumination, well balance uneven illumination. The modified system maintains its good rejecting performance, features better maintainability and operational convenience. Comparing with other image intensification algorithms, this method features better self-adaptability and faster processing speed and is more applicable to real-time intensification of color images.