Automatic image annotation is a very essential technology cause the huge development of the multimedia and Internet.Recently,many approaches change multi-label annotation problem to singlelabel annotation problem while they are always time-consuming and useless to some extent.In this paper,we propose an enhanced region semantic analysis algorithm for scenery images annotation.It contains segmentation,clustering and mapping processes.We use the classical segmentation algorithm: normalized cuts and cluster patches with feature weight selection.Finally we relate cluster centers and keywords using statistical method.Experimental results show that our algorithm achieves promising performance with the scenery images and outperforms region semantic analysis algorithm on the same benchmark datasets.