• Ms. Snehal Malode
• Ms. Pradnya Gajbhiye
• Ms. Priti Lokhande

Segmentation is the process of partitioning a digital image into multiple segments. In the field of Medical Imaging, segmentation of images is important because we need to create visual representations of internal structures of a body for proper diagnosis and treatment of diseases. Here three clustering based image segmentation algorithms namely K means, Fuzzy C-means and pillar K means are compared for the performance based on accuracy, execution time , number of iterations, area, standard deviation, variance and entropy. It is found that Pillar k means algorithm shows better performance in terms of accuracy, execution time etc

"Comparative Performance Analysis of clustering based Image segmentation algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 5, page no.49-53, May-2018, Available :http://www.jetir.org/papers/JETIR18IC010.pdf

"Comparative Performance Analysis of clustering based Image segmentation algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 5, page no. pp49-53, May-2018, Available at : http://www.jetir.org/papers/JETIR18IC010.pdf