• DocumentCode
    602032
  • Title

    A new approach of image inpainting based on PSO algorithm

  • Author

    Shu-Chiang Chung ; Ta-Wen Kuan ; Chuan-Pin Lu ; Hsin-Yi Lin

  • Author_Institution
    Dept. of Inf. Technol., Meiho Univ., Pingtung, Taiwan
  • fYear
    2013
  • fDate
    12-16 March 2013
  • Firstpage
    205
  • Lastpage
    209
  • Abstract
    In this paper, an efficient approach is developed to incorporate the exemplar-based image of inpainting method and the minimum error boundary of cut technique, that is proposed to improve the image inpainting in a more nature quality with high performance. The approach is based on the particle swarm optimization. Several advantages are addressed as follow. First, the image inpainting in texture with the linear structure is exploited to reasonably inpaint the damaged image in a high priority. Due to set the first priority to inpaint in the linear structure, such a method guarantees the integrality of the linear structure. In addition, the minimum error boundary of cut technique can effectively decrease the unnatural phenomena through inpainting the gap of damaged image. Owing to the damaged one will be dawdling extraordinarily if searching the similar block while inpainting. In this case, the method is proposed by joined the particle swarm optimization algorithm, and the outcome indeed improves the efficiency of image inpainting.
  • Keywords
    image texture; particle swarm optimisation; PSO algorithm; cut technique; exemplar-based image inpainting method; image inpainting approach; image texture; linear structure; minimum error boundary; particle swarm optimization algorithm; Algorithm design and analysis; Educational institutions; Equations; Mathematical model; PSNR; Particle swarm optimization; Vectors; Exemplar-Based Image Inpainting; Image Inpainting; Minimum Error Boundary Cut; Particle Swarm Optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Orange Technologies (ICOT), 2013 International Conference on
  • Conference_Location
    Tainan
  • Print_ISBN
    978-1-4673-5934-4
  • Type

    conf

  • DOI
    10.1109/ICOT.2013.6521193
  • Filename
    6521193