Published Paper Details:

Medical Images play a crucial role in disease diagnosis. Image segmentation is the process by which a digital image is partitioned into multiple segments (sets of pixels). The main purpose of image segmentation is to simplify the representation of an image so that it becomes easier when it comes to further image analysis, visualization, object representation, and other image processing tasks. Any type of image can be used for segmentation such as grayscale, color, motion, etc. Segmentation techniques are basically used to identify objects in an image for object-based measurements such as the size and shape of the object. In this paper, various techniques that are used for image segmentation are discussed and summarized by emphasizing their characteristics, advantages, and disadvantages. The methods discussed in this paper are thresholding methods, clustering methods, watershed segmentation, and edge-based segmentation techniques.