| Literature DB >> 22331852 |
Abstract
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√n(c)·N) in which K, n(c), 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.Mesh:
Year: 2012 PMID: 22331852 DOI: 10.1109/TPAMI.2012.47
Source DB: PubMed Journal: IEEE Trans Pattern Anal Mach Intell ISSN: 0098-5589 Impact factor: 6.226