2.4 Madhloom H.T. [14]
This paper reports the use of k-means clustering, active contours and Snake algorithm [15], watershed transform Fand many more .Watershed segmentation became a popular tool for different applications that require image segmentation, such as machine inspection, aerial image understanding, medical image analysis, and video object segmentation [17]. The watershed segmentation offers some advantages: it is a simple intuitive method, fast and can be parallelized and it produces a complete division of the image in separated regions, thus avoiding the need for any kind of contours joining [16]. Its significant drawbacks include over-segmentation and sensitivity to noise.