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1)  Harriscornerdetection
Harris检测
2)  Harris corner detection
Harris角点检测
1.
Research into the effects of image quality on Harris corner detection;
图像质量对Harris角点检测的影响研究
2.
In order to solve the problem of large distortion on InSAR images,based on comparison of several registration methods on SAR and optical sensors images,a robust algorithm composed of coarse registration,Harris corner detection,correlation matching,Delaunay Triangulation is proposed.
为了解决星载InSAR非相干图像配准中不同区域对应不同形变参数的问题,将几种传统的SAR图像配准和光学图像配准的方法有机结合,提出了一种基于概略配准、Harris角点检测、相关系数匹配、Delaunay三角网剖分插值映射的InSAR复图像精确配准方法。
3.
In this paper,a novel Harris corner detection algorithm based on condition number is proposed.
该方法在Harris算法提取角点的基础上,采用条件数定量地分析了噪声对确定图像间变换关系的影响程度,通过阈值设定筛选出具有良好稳定性的角点,克服了Harris角点检测可能存在的角点位置偏移和易受噪而提取出伪角点等问题。
3)  Harris corner detector
Harris角检测器
1.
Interest points are firstly extracted by Harris corner detector in two images and each interest point is assigned one dominant orientation.
提出了一种基于兴趣点方向特征的图像拼接算法IPOF(Interest Point Orientation Feature),该算法利用Harris角检测器提取出两幅图像的兴趣点并为每个兴趣点分配一个主方向,采用方向相关系数法提取出初始匹配对,根据特征点之间的关系去除伪匹配对,得到两幅图像的对应兴趣点特征对从而确定变换参数,最后使用加权平均的方法融合图像。
2.
Firstly, the interest points from two images were extracted by Harris corner detector, then the corresponding interest point pair of features were got by comparison maximum algorithm.
该方法首先利用Harris角检测器提取两幅图像中的兴趣点,并在此基础上采用比较最大值法提取出对应兴趣点特征对,最后利用这些匹配特征对来实现图像的拼接。
4)  Harris corner detector
Harris角点检测
1.
First it introduces how to combine the Harris corner detector and the Chen sub-pixel obtaining method to find the feature corner.
首先介绍如何结合Harris角点检测器和Chen的亚象素提取算法精确地求取特征点的亚象素位置,然后分析利用透视投影变换矩阵自动提取特征点位置,最后结合T-sai的标定方法给出了实验结果,验证了方法的有效性。
2.
First,detected the corner points which contain the main features of the object by using Harris corner detector.
首先,利用Harris角点检测算法提取表示目标主要特征的角点;其次,基于提取的角点,建立目标模型,将其嵌入Mean Shift 算法进行跟踪。
3.
The feature points from two images were extracted by Harris corner detector,then the corresponding feature point pairs were got by the cross-correlation of the gray scale around the feature points,and the mismatched pairs were eliminated based on the Eulerian distance of the transformation parameter vector.
提出了一种基于特征点的图像拼接算法,首先利用Harris角点检测提取两幅图像中的特征点,用特征点邻域灰度相关性将特征点进行匹配,并在此基础上根据变换参数向量的欧式距离对误匹配进行剔除,进而实现图像拼接。
5)  the Harris vertex examination
Harris焦点检测
6)  Harris-Laplace detector
Harris-Laplace检测子
1.
This valid parameter interval greatly increases the keypoint number detected by Harris-Laplace detector.
这个有效的参数区间大大增加了Harris-Laplace检测子所能获取的稳定关键点的数目。
补充资料:HA
   CAS号  1415-93-6
    性质  黑褐色或棕黑色无定形粉末。呈弱酸性,溶于碱,难溶于酸,有亲水性、离子交换性、络合性、分散性等综合性能。可聚合,其聚合物(聚腐殖酸)有耐热、耐盐性能。
     用途  用于蓄电池极板负极添加剂。
   包装储运  内衬塑料袋、外套编织袋包装,每袋25kg。贮存于阴凉、干燥、通风的库房内。防潮、防雨。搬运时轻装轻卸,以防包装破损。按一般化学品规定贮运。
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