• Title/Summary/Keyword: Byasian Statistical Approach

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A Flexible Line-Fitting ICM Approach for Takbon Image Restoration (유연한 선부합 ICM 방식에 의한 탁본영상복원)

  • Hwang, Jae-Ho
    • The KIPS Transactions:PartB
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    • v.13B no.5 s.108
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    • pp.525-532
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    • 2006
  • This paper proposes a new class of image restoration on the Ising modeled binary 'Takbon' image by the flexible line-fitting ICM(Iterated conditional modes) method. Basically 'Takbon' image need be divided into two extreme regions, information and background one due to its stroke combinations. The main idea is the line process, comparing with the conventional ICM approaches which were based on partially rectangular structured point process. For calculating geometrical mechanism, we have defined line-fitting functions at each current pixel array which form the set of linear lines with gradients and lengths. By applying the Bayes' decision to this set, the region of the current pixel is decided as one of the binary levels. In this case, their statistical reiteration for distinct tracking between intra and extra region offers a criterion to decide the attachment at each step. Finally simulations using the binary 'Takbon' image are provided to demonstrate the effectiveness of our new algorithm