Performance Evaluation of Image Segmentation using Fuzzy C Means Clustering

  Sneha P. Shah,  Sweety Maniar,  Sheron H.Christy

The use of image segmentation is to partition an image into meaningful regions with respect to a particular application. The application of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. The result of image segmentation is a set of segments that collectively cover the entire image. Every pixels in a region are similar with respect to some characteristic or computed property, such as color ,intensity..etc. The purpose of clustering is to identify natural groupings of data from a large data set to produce a concise representation of a system's behavior. Fuzzy c-means is a data clustering technique in which a dataset is grouped into n clusters with every data point in the dataset belonging to every cluster to a certain degree.

Keywords- Image segmentation ,fuzzy c means clustering, mutual Information

Unique Identification Number - IJEDR1401012
Page Number(s) - 57-59
Pubished in - Volume 2 | Issue 1 | March 2014
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Sneha P. Shah,  Sweety Maniar,  Sheron H.Christy,   "Performance Evaluation of Image Segmentation using Fuzzy C Means Clustering", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.2, Issue 1, pp.57-59, March 2014, Available at :http://www.ijedr.org/papers/IJEDR1401012.pdf