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harris corner
相关语句
  harris角点
     Improved Harris Corner Detection Algorithm Based on B-spline
     基于B样条的改进型Harris角点检测算法
短句来源
     Harris corner detection based on theory of scale-space
     基于尺度空间理论的Harris角点检测
短句来源
     The theories and implemental methods of SUSAN operator, MIC operator and Harris operator were compared and Harris corner detection was finished by the tool of VC6.0 in the thesis.
     该文对比SUSAN算子、MIC算子和Harris算子的原理及实现方法,使用VC6.0编程工具,完成图像的Harris角点检测。
短句来源
     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
短句来源
     Harris corner detection is based on the pixel gradient of the image,which is restricted to the relativities between the pixels.
     Harris角点检测计算的依据是图像像素点的梯度,并且受约于像素之间的相关性.
短句来源
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  “harris corner”译为未确定词的双语例句
     This paper proposes a novel algorithm for image mosaic based on interest points. Interest points are firstly extracted by Harris corner detector in two images and each interest point is assigned one dominant orientation. Using orient correlative coefficient matching method to extract the initial matches,then reject the false match according to the relationship among feature points.
     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。
短句来源
     IMPROVING HARRIS CORNER DETECTOR
     改进Harris算子用于点特征的精确定位
短句来源
     3. The algorithms of the image coordinate extraction of the pseudo-random color encoded pattern based on Harris corner detect and model matching method are implemented.
     三 实现基于Harris角探测和模板匹配法的彩色伪随机编码模板的图像特征点提取算法。
短句来源
     The interest point in the image can be obtained by Harris corner detector.
     而图像的特征点提取可以采用简单而稳定的Harris角测量。
短句来源
     In this paper, the coarse-to-fine scheme is adopted and all the necessary corners can be obtained quickly and accurately through integration of Radon transform, Harris corner detector and Forstner detector.
     该方法采用由粗到精的多层次检测策略,通过综合使用Radon变换、Harris算子以及Forstner算子,能够快速准确地提取出图像中的棋盘点。
短句来源
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  相似匹配句对
     IMPROVING HARRIS CORNER DETECTOR
     改进Harris算子用于点特征的精确定位
短句来源
     Harris corner detection based on theory of scale-space
     基于尺度空间理论的Harris角点检测
短句来源
     English Corner
     英语笑谈
短句来源
     Chinese Corner
     汉语角
短句来源
     It is compared with Harris' s formula .
     导出了低脆性岩石N-K_1关系的一般表达式,并与Harris公式进行了比较.
短句来源
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  harris corner
It consists of two schemes: (1)?extracting robust point and line features from sonar data and (2)?recognizing planar visual objects using a multi-scale Harris corner detector and its SIFT descriptor from a pre-constructed object database.
      
The Harris corner detector is used for benchmarking.
      
Specifically, the performances of the SUSAN and the Harris corner detection algorithms have been compared.
      
We found out 50 most prominent interest points from each pair of images by using Harris corner detector.
      
We conducted Harris corner detection from set of pairs from the dataset we used.
      
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This paper compares two important corner detectors:Harris corner detector and Frstner corner detector.The author proposes an approach to use the advantages of both corner detectors,which is effective in detecting accurate interest points.

Harris算子是在计算机视觉领域使用非常广泛的点特征提取算子 ,它算法简单 ,而且稳定 ,但缺憾是其定位精度只能达到一个像素。参考摄影测量中F¨orstner算子精确定位的思想 ,改进Harris算子 ,使其可以定位到子像素。实验证明 ,该方法在点特征的提取和精确定位方面都达到了较好的效果。

A new algorithm for automatically extracting chessboard corners is presented. In this paper, the coarse-to-fine scheme is adopted and all the necessary corners can be obtained quickly and accurately through integration of Radon transform, Harris corner detector and Forstner detector. The algorithm has two traits relative to the traditional approach: the position of the corners can be determined automatically while not requiring manual interposition, and high precision could be...

A new algorithm for automatically extracting chessboard corners is presented. In this paper, the coarse-to-fine scheme is adopted and all the necessary corners can be obtained quickly and accurately through integration of Radon transform, Harris corner detector and Forstner detector. The algorithm has two traits relative to the traditional approach: the position of the corners can be determined automatically while not requiring manual interposition, and high precision could be acquired and the mean position error is below 0.1 pixels.

提出了一种自动获取棋盘角点的新算法。该方法采用由粗到精的多层次检测策略,通过综合使用Radon变换、Harris算子以及Forstner算子,能够快速准确地提取出图像中的棋盘点。与传统方法相比,该算法具有两个明显的优点:无须人工干预,能够自动确定角点位置;定位精度高,角点的平均位置偏差在0.1个像素以内。

In this paper, an automatic and robust image mosaic algorithm is presented. In this algorithm, Harris corner detector is used to extract feature points, which gains sub pixel precision for features extraction. Then, a pseudo matching set is obtained by comparing local neighborhoods of features through intensity cross correlation method and these pseudo matches are divided into inliers and outliers using robust RANSAC algorithm. In the inliers sub set, LM algorithm is used to estimate the point transformation...

In this paper, an automatic and robust image mosaic algorithm is presented. In this algorithm, Harris corner detector is used to extract feature points, which gains sub pixel precision for features extraction. Then, a pseudo matching set is obtained by comparing local neighborhoods of features through intensity cross correlation method and these pseudo matches are divided into inliers and outliers using robust RANSAC algorithm. In the inliers sub set, LM algorithm is used to estimate the point transformation matrix between two images accurately. In the end, the image color of the overlapping band is smoothed with bilinear interpolation technique. The whole algorithm is completed automatically. It filters the noisy or wrong input data iteratively, then estimates the model parameters through pure data, so it has strong error tolerant capacity for the image noise and inaccuracy of feature extraction. When estimating the model parameters, the energy function is constructed based on the position errors of features instead of the features' intensity errors, which conquers the original methods' shortcoming of sensitivity to illuminating conditions and makes this algorithm more practical. Experimental results show the image mosaic effect is wonderful and the algorithm is stable very much. It is high valuable in practice.

提出了一种全自动稳健的图像拼接融合算法。此算法采用 Harris角检测算子进行特征点提取 ,使提取的精度达到了亚像素级 ,然后以特征点邻域灰度互相关法进行特征点匹配得到了初步的伪匹配集合 ,并运用稳健的RANSAC算法将伪匹配点集合划分为内点和外点 ,在内点域上运用 L M优化算法精确地估计出了图像间的点变换关系 ,最后采用颜色插值对交接处进行颜色过渡。整个算法自动完成 ,它对有较大误差或错误的特征点数据迭代过滤 ,并用提纯后的数据来做模型估计 ,因而对图像噪声和特征点提取不准确有强健的承受能力。在参数估计时 ,以特征点的坐标位置误差而不是亮度误差来构造优化函数 ,克服了以往算法对光照的敏感性 ,使算法更具有实用性。实验结果表明 ,该算法融合效果比较理想 ,鲁棒性强 ,具有较高的使用价值

 
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