Differential microphone arrays have become a promising method to address multiple sound source localization. Among the differential microphone arrays, the existing typical method is the histogram approach, which utilizes the time-frequency sparseness characteristic of speech signals. A direction-finding algorithm for multiple sound sources by the short-time average complex sound intensity estimation is proposed based on time-frequency masking and fuzzy clustering. The frequency bounds for time-frequency masking under various array sizes are also discussed. The advantages of the proposed method are that it has closed-form solution, superior to the histogram approach, and also less sensitive to array size. Based on the idea of time-frequency masking, an improved histogram approach is also presented. The performance of the proposed methods is verified by simulation results under noisy and reverberant environment.