• Title/Summary/Keyword: Iterative End-Point Fit Algorithm

Search Result 2, Processing Time 0.016 seconds

MBO-Tree: A Hierarchical Representation Scheme for Shapes with Natural Approximation and Effective Localization (MBO-Tree: 형상의 자연스러운 근사화와 효과적인 지역화를 지원하는 계층적 표현 방법)

  • 허봉식;김동규;김민환
    • Journal of Korea Multimedia Society
    • /
    • v.5 no.1
    • /
    • pp.18-27
    • /
    • 2002
  • A hierarchical representation scheme for planar curves, MBO-tree, is proposed in this paper, which provides natural approximation and efficient localization. MBO-tree is based on the Douglas-Peucker algorithm (iterative end-point fit algorithm), but approximation errors that are stored with corresponding points in MBO-tree nodes and are used for abstraction measures are adjusted by force to eliminate unnatural approximation. The error adjusting is just making the approximation error of a node in a MBO-tree to be less than or equal to that of its parent. In point of localization, the bounding area of a curve is represented with a minimum bounding octangle (MBO), which can enclose the curve more compactly compared with those of other hierarchical schemes, such as the strip tree, the arc tree and the HAL tree. The MBO satisfies the hierarchical inclusion property that is useful for hierarchical geometrical operations, such as the point-inclusion test and the polygon intersection test. Through several experiments, we found that the proposed scheme was able to approximate more naturally and to localize more effectively.

  • PDF

2D LiDAR based 3D Pothole Detection System (2차원 라이다 기반 3차원 포트홀 검출 시스템)

  • Kim, Jeong-joo;Kang, Byung-ho;Choi, Su-il
    • Journal of Digital Contents Society
    • /
    • v.18 no.5
    • /
    • pp.989-994
    • /
    • 2017
  • In this paper, we propose a pothole detection system using 2D LiDAR and a pothole detection algorithm. Conventional pothole detection methods can be divided into vibration-based method, 3D reconstruction method, and vision-based method. Proposed pothole detection system uses two inexpensive 2D LiDARs and improves pothole detection performance. Pothole detection algorithm is divided into preprocessing for noise reduction, clustering and line extraction for visualization, and gradient function for pothole decision. By using gradient of distance data function, we check the existence of a pothole and measure the depth and width of the pothole. The pothole detection system is developed using two LiDARs, and the 3D pothole detection performance is shown by detecting a pothole with moving LiDAR system.