International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 03 Issue: 12 | Dec -2016 www.irjet.net p-ISSN: 2395-0072 © 2016, IRJET | Impact Factor value: 4.45 | ISO 9001:2008 Certified Journal | Page 1565 A SURVEY : On Image Segmentation And Its Various Techniques Ashish Semwal 1 , Mukesh Chandra Arya 2 , Akshay Chamoli 3 , Upendra Bhatt 4 , Ashish Semwal & Mukesh Arya ,Ex M.tech Scholar G.B.P.E.C,Pauri Garhwal,Uttarakhand,India Upendra Bhatt, Faculty, CSED HNBGU Srinagar Garhwal, Uttarakhand, India Akshay Chamoli, Ex M.tech Scholar, CSED Central University Pondicherry, Pondicherry, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Image Segmentation is considered as one of the main steps in image processing. It divides a digital image into multiple regions in order to analyze them. It is also used to distinguish different objects in the image. In segmentation, we simply represent the image into more understandable form. Segmentation basically used to detect the objects, boundaries and other relevant data in the digital images. There are different approaches to implement segmentation like threshold, clustering and transform methods etc. After performing these approaches, the resultant segmented image is a collective pixel set of the entire image. Pixels in the image corresponds to some characteristics of image like color, texture etc.This paper presents a literature review of basic image segmentation techniques from last five years. Recent research in each of image segmentation technique is presented in this paper. Key Words: Fuzzy,MIA, Threshold, Clustering, Segmentation, PDE based image segmentation. 1.INTRODUCTION Image segmentation is an important topic in the field of digital image processing. The purpose of image segmentation is to partition the image into essential regions with respect to the appropriate locations. For the segmentation we need the Images. But the images are either in form of black and white or color. Color images are due to the grey level [1]. Famous techniques of image segmentation which are still being used by the researchers are Edge Detection, Threshold, Histogram, Region based methods, and Watershed Transformation. Since images are divided into two types on the basis of their color, i.e. gray scale and color images. Therefore image segmentation for color images is totally different from gray scale images, e.g., content based image retrieval[2], [3]. Also which algorithm is robust and works well is depends on the type of image [4].As the grey level contrast changes the color of color image also changes. Image segmentation plays important role in segmentation of medical images. Medical images play vital role in assisting health care which provides health care access patients for treatment. For the medical images, segmentation is crucial as a follows by first step in Medical Image Analysis (MIA) [5]. Digital image segmentation is an important and recent domain in computer history and digital image processing. Several techniques of it has been developed by Bell Labs, University of Maryland and few other places in 1960. Concept of image segmentation is applicable to medical imaging, video phone, photo enhancement, satellite imagery etc. in the field of medical imaging, is difficult to implement proper segmentation because of facing some problems like size of brain, head, leg, type of disease etc. so, to solve these problems, we need different algorithm to segment these image to acquire accurate results. The concept of fuzzy logic, pattern recognition and machine learning has been combined with artificial intelligence in digital image processing. Image techniques can be clubbed together in a general framework called Image Engineering. Image Engineering can be defined as that which contains three layers as: a) Image understanding b) Image Analysis c) Image Processing Figure 1: Layers of Image Engineering 2. LITERATURE REVIEW OF IMAGE SEGMENTATION TECHNIQUES There are different techniques of image segmentation. Some of which are following: Fig: Image segmentation techniques