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Finding arbitrary shaped clusters and color image segmentation

Soleymani Baghshah, M ; Sharif University of Technology | 2008

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  1. Type of Document: Article
  2. DOI: 10.1109/CISP.2008.761
  3. Publisher: 2008
  4. Abstract:
  5. One of the most famous approaches for the segmentation of color images is finding clusters in the color space. Shapes of these clusters are often complex and the time complexity of the existing algorithms for finding clusters of different shapes is usually high. In this paper, a novel clustering algorithm is proposed and used for the image segmentation purpose. This algorithm distinguishes clusters of different shapes using a two-stage clustering approach in a reasonable time. In the first stage, the mean-shift clustering algorithm is used and the data points are grouped into some sub-clusters. In the second stage, connections between sub-clusters are established according to a dissimilarity measure and final clusters are formed. Experimental results show the ability of the proposed algorithm for finding clusters of arbitrary shapes in synthetic datasets and also for the segmentation of color images. © 2008 IEEE
  6. Keywords:
  7. Algorithms ; Cluster analysis ; Clustering algorithms ; Color ; Color image processing ; Digital image storage ; Flow of solids ; Image enhancement ; Image processing ; Image segmentation ; Optical properties ; Optimal control systems ; Signal processing ; Stages ; Arbitrary shapes ; Clustering approach ; Color image segmentation ; Color imaging ; Color spaces ; Data points ; Dissimilarity measures ; International congresses ; Mean-shift clustering ; Novel clustering ; Reasonable time ; Sub-clusters ; Synthetic datasets ; Time complexities ; Two stages ; Chlorine compounds
  8. Source: 1st International Congress on Image and Signal Processing, CISP 2008, Sanya, Hainan, 27 May 2008 through 30 May 2008 ; Volume 1 , 2008 , Pages 593-597 ; 9780769531199 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/4566224