The objective of this paper is to develop an effective robust fuzzy c-means clustering brain images. Local mesh patterns feature extractor is proposed for medical image segmentation. The local region of image is represented by dataset, which are evaluated by taking into consideration the magnitude of local difference between the center pixel and its neighbors. First, image split in to sub blocks and novelobjectivefunction features are extracted from each given dataset.. Once the image has been split into blocks of roughly homogeneous texture, we apply an agglomerative procedure to merge similar adjacent regions until one of the two stopping criteria is satis1ed. At each stage we merge the pair of adjacent regions which have the largest merger importance value. Based on merger importance the regions are merged and then form the segmented regions for medical image segmentation application. Experimental results are tested on benchmark MRI database for medical image segmentation application. Results after being investigated, proposed method shows a significant improvement for segmentation of images.