Image processing plays a one of the important vital role in developing real world application is an Image Segmentation, which is used widely in Computer vision for the purpose of object tracking and to identify image boundaries. It aims at extracting meaningful objects lying in the image. Generally there is no unique method or approach for image segmentation The different algorithms used in Image segmentation are Clustering-based, Region-based and Edge based. Image segmentation is the division or separation of an image into multiple segments i.e. set of pixels, pixels in a region are similar according to some criterion such as color, intensity or texture. This paper gives the view about the methods in image segmentation such as thresholding, k-means clustering, grab-cut method and graph -cut method. Every method is discussed along with its advantage and disadvantages which helps us in deciding which the best and efficient method of image segmentation is. The main aim of the paper is to come out with the more efficient method in image segmentation which can be used for real world application development.