• DocumentCode
    1050390
  • Title

    Optimal decomposition of convex morphological structuring elements for 4-connected parallel array processors

  • Author

    Park, Hochong ; Chin, Roland T.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA
  • Volume
    16
  • Issue
    3
  • fYear
    1994
  • fDate
    3/1/1994 12:00:00 AM
  • Firstpage
    304
  • Lastpage
    313
  • Abstract
    A morphological operation using a large structuring element can be decomposed equivalently into a sequence of recursive operations, each using a smaller structuring element. However, an optimal decomposition of arbitrarily shaped structuring elements is yet to be found. In this paper, we have derived an optimal decomposition of a specific class of structuring elements-convex sets-for a specific type of machine-4-connected parallel array processors. The cost of morphological operation on 4-connected parallel array processors is the total number of 4-connected shifts required by the set of structuring elements. First, the original structuring element is decomposed into a set of prime factors, and then their locations are determined while minimizing the cost function. Proofs are presented to show the optimality of the decomposition. Examples of optimal decomposition are given and compared to an existing decomposition reported by Xu (1991)
  • Keywords
    array signal processing; image reconstruction; mathematical morphology; optimisation; parallel processing; 4-connected parallel array processors; convex morphological structuring elements; cost function minimization; optimal decomposition; recursive operation sequence; Computational efficiency; Cost function; Image analysis; Image coding; Image edge detection; Image processing; Morphological operations; Morphology; Object recognition; Shape;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.276129
  • Filename
    276129