Fast Superpixel Segmentation with Deep Features

  • Mubinun Awaisu
  • Liang LiEmail author
  • Junjie Peng
  • Jiawan Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11542)


In this paper, we propose a superpixel segmentation method which utilizes extracted deep features along with the combination of color and position information of the pixels. It is observed that the results can be improved significantly using better initial seed points. Therefore, we incorporated a one-step k-means clustering to calculate the positions of the initial seed points and applied the active search method to ensure that each pixel belongs to the right seed. The proposed method was also compared to other state-of-the-art methods quantitatively and qualitatively, and was found to produce promising results that adhere to the object boundaries better than others.


Superpixel Deep feature extraction Active search 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Mubinun Awaisu
    • 1
  • Liang Li
    • 1
    • 2
    Email author
  • Junjie Peng
    • 1
  • Jiawan Zhang
    • 1
  1. 1.College of Intelligence and ComputingTianjin UniversityTianjinChina
  2. 2.Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric EngineeringChina Three Gorges UniversityYichangChina

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