Using the enhanced fuzzy C-means（ En FCM） clustering algorithm for image segmentation can greatly improve the efficiency of the algorithm. However

due to lack of using spatial information of the image

results in En FCM algorithm is more sensitive to the salt and pepper noise

and the segmentation results are not accurate. So an En FCM clustering method based on Euclidean space distance is proposed. The reciprocal of the Euclidean space distance of neighbor pixels and to central pixel in image acts as weight for weighing with neighbor pixel

to introduce spatial and neighbor information. Result is summed with the central pixel to filter the original image.Clustering operation is carried out on gray histogram of image

get the segmentation result. Filtering function of Euclidean space distance is introduced

not only consider neighborhood information

but also spatial information at the same time

and effectively suppress the influence of noise in the clustering process. The experimental results show that

comparing with En FCM algorithm

the proposed method is more robust to the salt and pepper noise and more ideal segmentation result can be obtained.