Description: 提出了一种基于特征点的全自动无缝图像拼接方法。该方法采用对于尺度具有鲁棒性的SIFT算法进行特征点的提取与匹配，并通过引导互匹配及投票过滤的方法提高特征点的匹配精确度，使用稳健的RANSAC算法求出图像间变换矩阵H的初值并使用LM非线性迭代算法精炼H，最终使用加权平滑算法完成了图像的无缝拼接。-Based on feature points of automatic seamless image mosaic method. The method used for the scale robust algorithm SIFT feature point extraction and matching, and guide each other through the match and voting methods of filtering feature point improve matching accuracy, the use of robust RANSAC algorithm between images obtained transformation matrix H the initial value and use the LM non-linear iterative algorithm refining H, end-use-weighted smoothing algorithm to complete the image of the seamless splicing. Platform: |
Size: 151552 |
Author:小兔兔牙 |
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Description: ransac是常用的稳健计算机视觉的方法，可用于两幅影像的配准.-RANSAC is a commonly used method of robust computer vision, two images can be used for registration. Platform: |
Size: 743424 |
Author:jiaojiao |
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Description: SIFT特征提取演算法(包含匹配以及除错机制RANSAC)-可用于两张影像之特征点匹配
-SIFT feature extraction algorithm (including the match, as well as debug mechanisms RANSAC)- can be used for two images of the feature points matching Platform: |
Size: 11264 |
Author:qwe |
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Description: (1) 读取n副连续有重叠部分的图像，在n副图像中检测SIFT特征，并用SIFT
特征描述子对其进行描述。
(2) 匹配相邻图像的特征点，并根据特征点向量消除误匹配。
(3) 使用RANSAC方法，确定变换参数。
(4) 图像融合
-(1) Read n successive overlapping sub-part of the image, the image of the n sub-SIFT features detected and characterized using SIFT descriptors be described. (2) adjacent to the image feature point matching, and according to the feature vector to eliminate false matching points. (3) using RANSAC approach to determine the transformation parameters. (4) image fusion Platform: |
Size: 4096 |
Author:石梦鑫 |
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Description: 利用sift算法提取两张图像的特征点，利用ransac去除误匹配，最后将两张图片拼接在一起(Using sift algorithm to extract the two feature points of the image, the use of ransac to remove the wrong match, and finally the two pictures together) Platform: |
Size: 358400 |
Author:ruiruihaha
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