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Image segmentation is the process of dividing a digital image into number of segments. The main goal of segmentation is to simplify the representation of an image that is more useful and easier to analyze. Image segmentation is a set of small segments that makes the entire image. Each of the pixels are similar with respect to some characteristic property such as color, texture etc. some of major applications of image segmentation are content based image retrieval, machine vision, medical imaging, computer tomography and magnetic resonance imaging, surgery planning, virtual surgery simulation, object detection, face detection, face recognition, fingerprint recognition, iris recognition. The widely used method of image segmentation is known as thresholding method. This method is based on threshold value to convert grayscale image into binary image. To select a threshold value various methods are available maximum entropy method, balanced histogram thresholding, hybrid thresholding, Otsu’s method or maximum variance and k-means clustering. Motion and interactive segmentation that relies on motion in the image to perform segmentation. It finds out the differences between a pair of images. Histogram based methods are very efficient as compare to other segmentation methods. They require only one pass through the pixels. In this a histogram is computed from all the pixels in the image, and the peak and valleys in the histogram are used to locate the clusters in the image. Edge detection is a well developed field on its own image processing. Edges and boundaries of the regions are closely related to each other. There is often sharp adjustment in intensity at the region boundaries. Region growing methods rely on the assumption of neighboring pixels with one region have similar values. SRS (Statistical Region Merging) starts by building the graph of pixels with 4 connectedness with edges weighted by the absolute value of the intensity difference. Each pixel forms a single pixel region. SRM then sorts those edges in a propriety queue and decides whether or not to merge the current regions belonging to the edges pixels with statistical predicate.