This paper presents an efficient dynamic and run-time Hardware/Software scheduling approach. This scheduling heuristic consists in mapping online the different tasks of a highly dynamic application in such a way that the total execution time is minimized. We consider soft real-time data flow graph oriented applications for which the execution time is function of the input data nature. The target architecture is composed of two processors connected to a dynamically reconfigurable hardware accelerator. Our approach takes advantage of the reconfiguration property of the considered architecture to adapt the treatment to the system dynamics. We compare our heuristic with another similar approach. We present the results of our scheduling method on several image processing applications. Our experiments include simulation and synthesis results on a Virtex V-based platform. These results show a better performance against existing methods.