Various Image Segmentation Techniques through Clustering and Markovian Model: A Survey
Ram Kishan Dewangan1, Tripti Sharma2
1Ram Kishan Dewangan, Computer Science & Engineering, Chhattishgarh Swami Vivekanand Technical University/ Chhattrapati Shivaji Institute of Technology, Durg, India.
2Ms. Tripti Sharma, Computer Science & Engineering, Chhattishgarh Swami Vivekanand Technical University/Chhatrapati Shivaji Institute of Technology, Durg, India.
Manuscript received on january 17, 2012. | Revised Manuscript received on February 05, 2012. | Manuscript published on February 29, 2012. | PP: 183-185 | Volume-1 Issue-3, February 2012. | Retrieval Number: C0217021312/2011©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Image segmentation is the identification and separation of homogeneous regions in the image, has been the subject of considerable research activity. Many algorithms have been elaborated for gray scale images. This paper is a survey on different clustering techniques to achieve image segmentation. Clustering can be termed here as a grouping of similar images in the database. Clustering is done based on different attributes of an image such as size, color, texture etc. The purpose of clustering is to get meaningful result, effective storage and fast retrieval in various areas.
Keywords: Clustering, image segmentation, markovian model, relevance feedback