Testing image processing applications is very ressource consuming. Many complex images have to be generated as test inputs and the expected resulting outputs have to be determined to complete the test cases. The present paper deals with this challenge in testing implementations of image operations, namely dilation. It applies random testing using models from stochastic geometry for random input generation. The Statistical Oracle, a modification of the well-known Heuristic resp. Parametric Or- acle, is used to compare the results. Therefore, reliability predictions are also possible.