Image processing system for monitoring of conveyor belt systems

A prototype of an image processing system for the monitoring of conveyor belt systems in video real time is described. To avoid completely hazardous situations, special requirements on the robustness and the computational efficiency of the system under heavy climatic and illumination conditions have to be met. For the computation of the belt loading and the position of the conveyed masses the profile of the loaded belt is subtracted from a stored profile of the empty belt. Both empty and loaded belt profiles are estimated using the triangulation principle. A model based algorithm combined with a two-step classificator is applied to detect large stones or other bulky objects from a sequence of profiles. The gray level characteristics of the conveyed masses are computed, using features derived from the ID histogram. The structure of the masses is evaluated using a modified fractal operator. One class out of a predefined set of classes is selected. Image processing hardware based on the digital signal processor TMS320C30 is applied.