Performance comparison of the MOI, the COA, and the MOM methods in the application of JPEG

In this work, the performance of the MOI (mean-of inversion) method with respect to accuracy and convergence speed is compared with that of the COA (center-of-area) and the MOM (mean-of-maximum) methods in the application of JPEG (joint photographic experts group). The feature of the MOI method is that it defuzzifies each fired rule individually instead of superimposing fired rules before defuzzification. As a result, the MOI method is less sensitive to the contents of decision tables. The simulation results based on 15 USC pictures indicate that the MOI method has the best performance on accuracy and ties the COA method in the aspect of convergence speed. The MOM method has the worst performance on both aspects of accuracy and convergence speed