A robust approach to edge detection of scanned point data

Y. Lee, S. Park, Y. Jun, W. C. Choi

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)


In reverse engineering, segmentation is used to divide a point data set into subsequent regions according to its shape. It is vital for interpretation of discrete scanned data since surface reconstruction can be accomplished one-by-one on a given region. Edge detection is crucial to the segmentation process. The level of edge detection depends on the complexity of the part, and it determines the eventual success or failure of the reverse engineering (RE) process. This paper proposes a novel approach to the edge detection of 3D points based on a region growing technique. The proposed algorithm consists of two parts. First, polygonal meshes are generated to the scanned point data using the Delaunay triangulation algorithm. Second, the normal vector and the area of a polygonal mesh are checked to find boundary meshes using cost criteria (angle criterion and area criterion) based upon a region growing technique. The region growing technique aggregates meshes into a region until the area of aggregated meshes reaches an area threshold from a series of seed meshes. The proposed edge detection method is found to be effective when compared with other methods.

Original languageEnglish
Pages (from-to)263-271
Number of pages9
JournalInternational Journal of Advanced Manufacturing Technology
Issue number3-4
Publication statusPublished - 2004


  • Cost criteria
  • Edge detection
  • Region-growing
  • Reverse engineering

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering


Dive into the research topics of 'A robust approach to edge detection of scanned point data'. Together they form a unique fingerprint.

Cite this