English  |  正體中文  |  简体中文  |  Items with full text/Total items : 57310/90918 (63%)
Visitors : 13014027      Online Users : 209
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/59952

    Title: Optimizing Region of Support for Boundary-Based Corner Detection: A Statistic Approach
    Authors: Horng, Wen-Bing;Chen, Chun-Wen
    Contributors: 淡江大學資訊工程學系
    Keywords: Corner detection;Discriminant criterion;Optimization;Region of support;Variance analysis
    Date: 2009-10
    Issue Date: 2011-10-05 22:29:56 (UTC+8)
    Publisher: Tokyo: Denshi Jouhou Tsuushin Gakkai
    Abstract: Boundary-based corner detection has been widely applied in spline curve fitting, automated optical inspection, image segmentation, object recognition, etc. In order to obtain good results, users usually need to adjust the length of region of support to resist zigzags due to quantization and random noise on digital boundaries. To automatically determine the length of region of support for corner detection, Teh-Chin and Guru-Dinesh presented adaptive approaches based on some local properties of boundary points. However, these local-property based approaches are sensitive to noise. In this paper, we propose a new approach to find the optimum length of region of support for corner detection based on a statistic discriminant criterion. Since our approach is based on the global perspective of all boundary points, rather than the local properties of some points, the experiments show that the determined length of region of support increases as the noise intensity strengthens. In addition, the detected corners based on the optimum length of region of support are consistent with human experts' judgment, even for noisy boundaries.
    Relation: IEICE Transactions on Information and Systems E92-D(10), pp.2103-2111
    DOI: 10.1587/transinf.E92.D.2103
    Appears in Collections:[資訊工程學系暨研究所] 期刊論文

    Files in This Item:

    File Description SizeFormat
    0916-8532_E92-D(10)p2103-2111.pdf9044KbAdobe PDF195View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback