This paper presents a new normalized frequency domain approach for adaptive blind equalization for multiple-input multiple-output (MIMO) communication systems. We first develop a time domain block based algorithm that updates the equalizer coefficients once per block of data symbols. As the time domain algorithm involves infinite summations in the separation cost function, an approximation is then proposed to reduce the cost function to finite summations. As a consequence, the block based time domain algorithm can be implemented in the frequency domain to reduce the computational complexity associated with the conventional symbol-by-symbol time domain update. Furthermore, by recognizing that the signals in the frequency domain are orthogonal, it is possible to significantly improve the convergence rate by normalizing the update equations with respect to the signal power in each frequency bin. Simulation results show that the proposed algorithm can successfully equalize the received signals while maintaining low computational complexity. Moreover, the presented normalized frequency domain blind equalization algorithm for MIMO systems significantly improves the convergence rate.