Segmentation Techniques Comparison in Image Processing

In day-to-day life, new technologies are emerging in the field of Image processing, especially in the domain of segmentation. This paper presents a brief outline on some of the most common segmentation techniques like thresholding, Model based, Edge detection, Clustering etc., mentioning its advantages as well as the drawbacks. Some of the techniques are suitable for noisy images. In that Markov Random Field (MRF) is the strongest method of noise cancellation in images whereas thresholding is the simplest technique for segmentation.