There are various uncertainties in the applications in many fields such as image processing and pattern recognition. However, the fuzzy ??-means(FCM) algorithm which is widely used in these fields cannot handle the uncertainties well. The introduction of interval type-2 fuzzy theory into FCM can bring such algorithm the ability of handling uncertainties, but the complexity of algorithm will increase accordingly. In order to reduce the complexity, an enhanced interval type-2 FCM algorithm is proposed. The initialization of cluster center and the process of type-reduction are optimized in this algorithm, which can greatly reduce the calculation of interval type-2 FCM and accelerate the convergence of the algorithm. The experimental results on random data and real data show the effectiveness of our proposed algorithm.