Medical Image segmentation is the most important step in extracting information from medical images. Segmentation of pulmonary Chest Computed Tomography (CT) images is a precursor to most of the pulmonary image analysis schemes. The purpose of lung image segmentation is to separate the voxels corresponding to lung tissue from the anatomy of the surrounding. In this paper, an automated image segmentation method has been proposed inorder to segment the region of interest present in the CT Lung slices. The proposed approach utilizes Fuzzy logic with Earth Mover's Distance (FEMD) based refinement methods. The final segmented output is further refined by morphological based operators. The performance of the proposed method is compared with various segmentation methods such as Canny Sobel and Prewitt and we have obtained an average segmentation accuracy of 79.4091% for segmenting CT lung images.