Segmentation algorithms are widely used in image processing. These methods have different complexity values and the choice of reasonable methods decreases on large images. Especially on the medical images with large size, it may take days to perform segmentation in some methods. However, parallel implementation may eliminate the drawback of these algorithms to some extent. In this study, we propose to implement segmentation algorithms in parallel using Graphical Processing Unit. Using the proposed implementation, the computation time of the K-centers, K-means and DBSCAN algorithms were decreases 87, 642 and 2 times, respectively.