Tampered Image Reconstruction with Global Scene Adaptive In-Painting

  • Ravi Subban
  • Muthukumar Subramanian
  • Pasupathi Perumalsamy
  • R. Seejamol
  • S. Gayathri Devi
  • S. Selvakumar
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 264)


The objective of in-painting is to reconstruct the mislaid region of an image. This paper presents a new in-painting algorithm from the goodwill of Exemplar-based Greedy algorithms, which consist of two phases: making a decision of filling-in order and selection of good exemplars for the damaged regions. The proposed method overcomes these tribulations with the protection of edges, textures and also with lesser propagation error. This scheme upgrades the filling-in order that is based on the combination of priority terms, to encourage the early synthesis of linear structures. The subsequent contribution helps sinking the error propagation to an improved detection of outliers from the candidate patches. The proposed methodology is well suited in terms of both natural and artificial images with plausible output. This scheme dramatically outperforms earlier works in terms of both perceptual quality and computational efficiency.


Curvature Driven Delusion Exemplar based Approach Texture Synthesis Structure Synthesis 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ravi Subban
    • 1
  • Muthukumar Subramanian
    • 2
  • Pasupathi Perumalsamy
    • 3
  • R. Seejamol
    • 3
  • S. Gayathri Devi
    • 3
  • S. Selvakumar
    • 3
  1. 1.Dept of CSEPondicherry UniversityPondicherryIndia
  2. 2.Dept of CSENITPondicherryIndia
  3. 3.CITEMS UniversityTirunelveliIndia

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