Recently, a several new methods of image segmentation have been proposed for digital image processing. Segmentation of an image is defined as a process involve in image processing and this process is an important step for the analysis of an image which includes partitioning of the image that is digital into several segments. Image segmentation plays an important role in image analysis, feature extraction, and image interpretation for many applications. It has widespread applications in medical science, for example, classification of different tissues, identification of tumor, estimating size of tumor, surgical planning, atlas matching etc. Various methods for segmenting an image consist of transforming signals which are complex into simple images. In this paper, various methods for the segmentation of the image are investigated and various algorithms for the segmentation process are also highlighted, depending on the clustering techniques. According to the study, we have concluded that the clustering process methods are extensively applied for the segmentation of natural images, and are indeed the most effective technique for the segmentation of images. And, in this survey paper, certain notable clustering-based image segmentation techniques are also highlighted as well.
Volume 12 | 07-Special Issue
Pages: 701-707
DOI: 10.5373/JARDCS/V12SP7/20202160