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Features Detection on Industrial 3D CT Data

  • Thi-Chau Ma
  • Chang-soo Park
  • Kittichai Suthunyatanakit
  • Min-jae Oh
  • Tae-wan Kim
  • Myung-joo Kang
  • The-Duy Bui
Part of the Communications in Computer and Information Science book series (CCIS, volume 263)

Abstract

Features are significantly used as design elements to reconstruct a model in reverse engineering. This paper proposes a new method for detecting corner features and edge features in 3D from CT scanned data. Firstly, the level set method is applied on CT scanned data to segment the data in the form of implicit function having two values, which mean inside and outside of the boundary of the shape. Next, corners and sharp edges are detected and extracted from the boundary of the shape. The corners are detected based on Sobel-like mask convolution processing with a marching cube. The sharp edges are detected based on Canny-like mask convolution. In this step, a noisy removal module is included. In the paper, the result of detecting both features is presented.

Keywords

Reverse Engineering (RE) Computed Tomography (CT) Corner and Edge Features Detection Mask Convolution Noise Removal 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Thi-Chau Ma
    • 1
  • Chang-soo Park
    • 2
  • Kittichai Suthunyatanakit
    • 3
  • Min-jae Oh
    • 3
  • Tae-wan Kim
    • 3
  • Myung-joo Kang
    • 2
  • The-Duy Bui
    • 1
  1. 1.Lab.of Human Machine InteractionUniversity of Engineering and Technology, Vietnam National UniversityHanoiVietnam
  2. 2.Dep. of Mathematical SciencesSeoul National UniversitySeoulKorea
  3. 3.Dep. of Naval Architecture and Ocean EngineeringSeoul National UniversitySeoulKorea

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