Multimedia Tools and Applications

, Volume 71, Issue 3, pp 1013–1031 | Cite as

Optimized image resizing using flow-guided seam carving and an interactive genetic algorithm

  • Jong-Chul YoonEmail author
  • Sun-Young Lee
  • In-Kwon Lee
  • Henry Kang


In this paper, we introduce a novel method for content-aware image resizing based on flow-guided seam carving. It extends the existing seam carving framework by replacing the conventional energy field with a “structure-aware” energy field that takes into account the feature orientations in the image. Guided by this new energy field, our approach excels in preserving (i.e., avoiding the distortion of) important structures in the image, such as shape boundaries. We also present a simple user interface to further optimize the resizing result based on the genetic selection process among multiple resizing operators such as scaling, cropping, and flow-guided seam carving. We show that such simple user interaction, coupled with the genetic algorithm, dramatically increases the chances of producing the user-desired outcome.


Image resizing Structure-aware energy field Interactive genetic algorithm 



This study was supported by 2011 Research Grant form Kangwon National University and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2011-0028568).


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Jong-Chul Yoon
    • 1
    Email author
  • Sun-Young Lee
    • 2
  • In-Kwon Lee
    • 2
  • Henry Kang
    • 3
  1. 1.Department of Broadcasting Visual Arts Technology & EntertainmentKangwon National UniversitySamcheokKorea
  2. 2.Department of Computer ScienceYonsei UniversitySeoulKorea
  3. 3.Department of Computer ScienceUniversity of MissouriSt. LouisUSA

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