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文章基本信息

  • 标题:Harris Scale Invariant Corner Detection Algorithm Based on the Significant Region
  • 本地全文:下载
  • 作者:Wu Peng ; Xu Hongling ; Li Wenlin
  • 期刊名称:International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 印刷版ISSN:2005-4254
  • 出版年度:2016
  • 卷号:9
  • 期号:3
  • 页码:413-420
  • DOI:10.14257/ijsip.2016.9.3.35
  • 出版社:SERSC
  • 摘要:The traditional Harris corner detection algorithm is sensitive to scale change, corners detected throughout the entire image under complex background, thus extracting more false corners, lead to the follow-up of large amount of calculation and a high rate of error matching. To solve this problem, this paper proposes an optimized Harris corner detection algorithm. First, a significant region detection method is used to extract the target area, and take closing operation for the result figure, can effectively achieve target and background segmentation; second, scale invariant describing methods is applied to Harris algorithm, at the same time, combined with the non-maximum suppression methods to extract corners, get more right corners. Through experiment contrasts, the algorithm used in this paper can be improved more corner detection performance.
  • 关键词:Harris; Significant area; Scale invariant; Non-maximum suppression
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