Elliptical shaped object recognition via a Modified RANSAC with edge orientation curve's segmentation-merge

Yingdi Xie, Jun Ohya

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2 Citations (Scopus)

    Abstract

    In this paper we proposed a novel processing framework for elliptical object detection from single image. It is well known that single ellipse can be estimated from any combination of five boundary pixels. Our proposal is based on a Modified RANSAC, which performs detection by an iterative manner that randomly selecting five boundary pixels to construct an ellipse model; and evaluating the model's validity afterward. By taking into consideration that providing constraint for the sampling process can significantly improve the detection capability, toward the sampling process, we assign guidance by clustering boundary pixels according to a boundary curves' segment-reconnect strategy. In the experimental result section, we demonstrate that this proposal achieves advance in both computational efficiency and robustness, by comparing with RHT based method as well as human labeling results.

    Original languageEnglish
    Title of host publicationProceedings of the 9th IASTED International Conference on Visualization, Imaging, and Image Processing, VIIP 2009
    Pages33-40
    Number of pages8
    Publication statusPublished - 2009
    Event9th IASTED International Conference on Visualization, Imaging, and Image Processing, VIIP 2009 - Cambridge
    Duration: 2009 Jul 132009 Jul 15

    Other

    Other9th IASTED International Conference on Visualization, Imaging, and Image Processing, VIIP 2009
    CityCambridge
    Period09/7/1309/7/15

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    Keywords

    • Ellipse detection

    ASJC Scopus subject areas

    • Computer Vision and Pattern Recognition
    • Software

    Cite this

    Xie, Y., & Ohya, J. (2009). Elliptical shaped object recognition via a Modified RANSAC with edge orientation curve's segmentation-merge. In Proceedings of the 9th IASTED International Conference on Visualization, Imaging, and Image Processing, VIIP 2009 (pp. 33-40)