Literature DB >> 22331852

VCells: simple and efficient superpixels using Edge-Weighted Centroidal Voronoi Tessellations.

Jie Wang1, Xiaoqiang Wang.   

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


  3 in total

1.  Hierarchical level features based trainable segmentation for electron microscopy images.

Authors:  Shuangling Wang; Guibao Cao; Benzheng Wei; Yilong Yin; Gongping Yang; Chunming Li
Journal:  Biomed Eng Online       Date:  2013-06-28       Impact factor: 2.819

2.  A Segmentation Method for Lung Parenchyma Image Sequences Based on Superpixels and a Self-Generating Neural Forest.

Authors:  Xiaolei Liao; Juanjuan Zhao; Cheng Jiao; Lei Lei; Yan Qiang; Qiang Cui
Journal:  PLoS One       Date:  2016-08-17       Impact factor: 3.240

3.  Superpixel-based segmentation of muscle fibers in multi-channel microscopy.

Authors:  Binh P Nguyen; Hans Heemskerk; Peter T C So; Lisa Tucker-Kellogg
Journal:  BMC Syst Biol       Date:  2016-12-05
  3 in total

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