Issue No. 06 - June (2012 vol. 34)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPAMI.2012.47
Jie Wang , Dept. of Sci. Comput., Florida State Univ., Tallahassee, FL, USA
Xiaoqiang Wang , Dept. of Sci. Comput., Florida State Univ., Tallahassee, FL, USA
VCells, the proposed Edge-Weighted Centroidal Voronoi Tessellations (EWCVTs)-based algorithm, is used to generate superpixels, i.e., an oversegmentation of an image. For a wide range of images, the new algorithm is capable of generating roughly uniform subregions and nicely preserving local image boundaries. The undersegmentation error is effectively limited in a controllable manner. Moreover, VCells is very efficient with core computational cost at O(K√nc·N) in which K, nc, and N are the number of iterations, superpixels, and pixels, respectively. Extensive qualitative discussions are provided, together with the high-quality segmentation results of VCells on a wide range of complex images. The simplicity and efficiency of our model are demonstrated by complexity analysis, time, and accuracy evaluations.
image segmentation, computational complexity, computational geometry, image resolution, complexity analysis, VCells, superpixels, EWCVT, edge-weighted centroidal voronoi tessellations-based algorithm, image oversegmentation, local image boundaries, image undersegmentation, O(K√n<;sub>;c<;/sub>;·N), Image segmentation, Clustering algorithms, Algorithm design and analysis, Partitioning algorithms, Shape, Image color analysis, Computational efficiency, clustering., Superpixels, k-means, centroidal Voronoi tessellations, image segmentation, image labeling
Jie Wang and Xiaoqiang Wang, "VCells: Simple and Efficient Superpixels Using Edge-Weighted Centroidal Voronoi Tessellations," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 34, no. , pp. 1241-1247, 2012.