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[Author] Yu-Hua LEE(1hit)

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  • Parallel Algorithms for Higher-Dimensional Euclidean Distance Transforms with Applications

    Yuh-Rau WANG  Shi-Jinn HORNG  Yu-Hua LEE  Pei-Zong LEE  

     
    INVITED PAPER-Algorithms and Applications

      Vol:
    E86-D No:9
      Page(s):
    1586-1593

    Based on the dimensionality reduction technique and the solution for proximate points problem, we achieve the optimality of the three-dimensional Euclidean distance transform (3D_EDT) computation. For an N N N binary image, our algorithms for both 3D_EDT and its applications can be performed in O (log log N) time using CRCW processors or in O (log N) time using EREW processors. To the best of our knowledge, all results described above are the best known. As for the n-dimensional Euclidean distance transform (nD_EDT) and its applications of a binary image of size Nn, all of them can be computed in O (nlog log N) time using CRCW processors or in O (nlog N) time using EREW processors.