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基于双边滤波改进的Harris特征点检测
  • ISSN号：1003-5060
  • 期刊名称：《合肥工业大学学报：自然科学版》
  • 时间：0
  • 分类：TP391.41[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]
  • 作者机构：[1]合肥工业大学计算机与信息学院,安徽合肥230009, [2]合肥工业大学数学学院,安徽合肥230009
  • 相关基金：国家自然科学基金一广东联合基金重点资助项目（U1135003）
作者： 朱少何, 檀结庆[1,2]
关键词： Harris特征点, Harris-Laplace算子, 双边滤波, 尺度空间, 跟踪分组, Harris feature point, Harris-Laplace operator, bilateral filter, scale space~ tracking group
中文摘要：

经典的Harris特征点检测和Harris-Laplace特征点检测在传统的算法中占据重要的地位,但它们或在尺度或在冗余上仍存在问题,并且对弱的特征点不能很好地检测。为此,文章提出了一种改进的方法,在多尺度Harris检测特征点时用改进的双边滤波来替代传统的高斯滤波,而且在检测时对特征点进行分组,一组代表同一局部结构,然后在各组中选取一个自相关矩阵特征值最接近的点来代表这一结构。实验表明此方法能较好地定位特征点位置和去冗余特征点。

英文摘要：

Harris and Harris-Laplace methods have the limitations of scales or redundant feature points, and can not solve the weak feature points, even though they have occupied an important posi- tion in the traditional algorithm. In this paper, an improved method of checking the feature points with multi-scale Harris method using an improved bilateral filter to replace the Gauss ~ter is presen- ted, then the tracking and grouping is conducted while checking the feature points, so some points re- presenting the same local structure are divided into a group, and a point which has the closest eigen- values of the auto-correlation matrix is selected from each group to represent its structure. The exper- imental results show that the method can precisely detect feature points and remove redundant feature points.

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期刊信息
  • 《合肥工业大学学报：自然科学版》
  • 中国科技核心期刊
  • 主管单位:中华人民共和国教育部
  • 主办单位:合肥工业大学
  • 主编：何晓雄
  • 地址：合肥市屯溪路193号
  • 邮编：230009
  • 邮箱：XBZK@hfut.edu.cn
  • 电话：0551-2905639
  • 国际标准刊号：ISSN：1003-5060
  • 国内统一刊号：ISSN：34-1083/N
  • 邮发代号:26-61
  • 获奖情况:
  • 1999中国优秀高校自然科学学报,1997华东地区优秀期刊,1998安徽省优秀科技期刊,中国期刊方阵“双效”期刊
  • 国内外数据库收录:
  • 美国化学文摘（网络版）,美国数学评论（网络版）,德国数学文摘,美国剑桥科学文摘,中国中国科技核心期刊,中国北大核心期刊（2004版）,中国北大核心期刊（2008版）,中国北大核心期刊（2011版）,中国北大核心期刊（2014版）
  • 被引量:19655