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Color Based Segmentation Using Clustering Techniques
Deepali Jain,  Shivangi Chaudhary
Segmentation of an image defines as a process of partitioning the image into its constituent parts or similar objects. There are two approaches for image segmentation i.e. discontinuity based and similarity based. In this paper, color based segmentation on noisy image using K-means and Fuzzy c-means is shown. Images are the best means of conveying information. Image is in RGB color space, transforming it in LAB color space which is more compatible to human vision. Clustering is one of the best methods for segmentation even if the data is large. The main aim of this paper is to compare the performance of K-means and Fuzzy c-means techniques over the noisy image. The best results can be seen after finding the accuracy of the segmented images using clustering techniques.
Keywords- Image segmentation, k-means clustering, Fuzzy c-means clustering
Unique Identification Number - IJEDR1403015Page Number(s) - 2980-2984Pubished in - Volume 2 | Issue 3 | Sept 2014DOI (Digital Object Identifier) -    Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
Deepali Jain,  Shivangi Chaudhary,   "Color Based Segmentation Using Clustering Techniques"
, International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.2, Issue 3, pp.2980-2984, Sept 2014, Available at :http://www.ijedr.org/papers/IJEDR1403015.pdf