An Iterative Raster Scan Algorithm for Superpixel Segmentation

DOI IR (HANDLE) Open Access

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Description

We propose an iterative raster scan algorithm for superpixel segmentation, which is based on the K-means clustering algorithm. The proposed algorithm updates the class label of each pixel only at the boundaries of superpixels in a raster scan order, and refers to only two neighboring pixels per pixel for updating the variables. Therefore, the proposed algorithm is computationally efficient compared with existing methods. Experimental results show that the proposed algorithm generates compact and adherent superpixels in a finite number of iterations of the raster scan process.

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Details 詳細情報について

  • CRID
    1050299981545239296
  • DOI
    10.12792/jiiae.12.12
  • ISSN
    21878811
    21881758
  • HANDLE
    2324/7173592
  • Text Lang
    en
  • Article Type
    journal article
  • Data Source
    • IRDB
    • Crossref
    • KAKEN
    • OpenAIRE

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