Objectives. Image processing tools are often embedded in larger systems. Validation of image processing methods is important because the performance of such methods can have an impact on the performance of the larger systems and consequently on decisions and actions based on the use of these systems. Most validation studies compare the direct or indirect results of a method, with a reference that is assumed to be very close or equal to the correct solution. In this paper, we propose a model for defining and reporting reference-based validation protocols in medical image processing. Materials and Methods. The model was built using an ontological approach. Its components were identified from the analysis of initial publications (mainly reviews) on medical image processing, especially registration and segmentation, and from discussions with experts from the medical imaging community during international conferences and workshops. The model was validated by its instantiation for 38 selected papers that include a validation study, mainly for medical image registration and segmentation.