Clustering Based Blood Smear Image Segmentation Techniques

This work examines different clustering-based image segmentation algorithms that are currently in use. Image segmentation involves extracting valuable information from an image; this might include locating objects as you move about the region or looking for abnormalities in medical images. Due to the fact that image pixels are typically unlabeled, clustering is a widely used method for analyzing them. 

All of the major clustering algorithms have been reviewed, namely K-Means Clustering based, Watershed, Edge based and Region Based Segmentation Methods. Accuracy of each technique is compared with the existing techniques.

Keywords: Image Segmentation, K-Means Clustering, Watershed, Edge Based Segmentation, Region Based Segmentation