A Study on Various Image Segmentation Techniques

Abstract

Image processing means the image can be processed by digital computer. The image segmentation techniques are used to partitioning the image in to several parts for further processing. It is mostly useful for applications like image compression or object recognition, because for these types of applications, it is inefficient to process the whole image. The segmentation is based on pixel intensity values, colors, texture, etc. Various segmentation techniques like edge, threshold, region, clustering and neural network are involved in the effective image analysis. The efficiency of the segmentation process improved with the help of several algorithms, namely, active contour, level set, Fuzzy clustering and K-means clustering.  Segmentation techniques provides the requirement of the suitable enhancement method that supports both intensity and texture based segmentation for better results.