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: 本文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。整个处理过程完全自动地实现了对一组图像的无缝拼接，克服了传统图像拼接方法在尺度和光照变化条件下的局限性。实验结果验证了方法的有效性。-This paper presents a feature points based on automatic seamless image mosaic method. The method used for the scale of the SIFT algorithm is robust feature points extraction and matching, and guide each other through the match and voting filtering feature point matching method to improve the accuracy of the RANSAC algorithm for the robust transformation matrix H between the images obtained The initial and refined using the LM non-linear iterative algorithm H, the final completion of the weighted smoothing algorithm for seamless image. Completely automated the entire process of a group to achieve seamless image stitching, image stitching method to overcome the traditional scale and illumination changes in the conditions of the limitations. Experimental results demonstrate the effectiveness of the method. Platform: |
Size: 150528 |
Author:wenping |
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Description: Abstract—Constraining by cameras’ view-angles of the
outdoor monitoring systems, the panoramic digital images
fail to be obtained directly from photographing. A method is
proposed on the basis of the scale invariance feature
transform (i.e. SIFT) algorithm to stitch images captured by
the turning video cameras together to form panoramic
images. Based on the SIFT features and the retrofitted KD-
Tree structure, the BBF searching strategy is employed to
match feature points. Then in a post-processing pass, the
Ransac algorithm is adopted to remove the mismatching
feature points. Photos captured by a surveillance camera are
taken as the input to test the proposed method. According to
the test, the whole processing time of stitch is reduced while
the fidelity of resulting stitched panoramic images is
ensured.-Abstract—Constraining by cameras’ view-angles of the
outdoor monitoring systems, the panoramic digital images
fail to be obtained directly from photographing. A method is
proposed on the basis of the scale invariance feature
transform (i.e. SIFT) algorithm to stitch images captured by
the turning video cameras together to form panoramic
images. Based on the SIFT features and the retrofitted KD-
Tree structure, the BBF searching strategy is employed to
match feature points. Then in a post-processing pass, the
Ransac algorithm is adopted to remove the mismatching
feature points. Photos captured by a surveillance camera are
taken as the input to test the proposed method. According to
the test, the whole processing time of stitch is reduced while
the fidelity of resulting stitched panoramic images is
ensured. Platform: |
Size: 345088 |
Author:bou33aza |
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Description: 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。-An automatic seamless image mosaic method based on feature points is proposed. First a scale-invariant feature extracting algorithm SIFT is used for feature extraction and matching. In order to improve the accuracy of matching, guided complementary
matching and voting filter is used. Then, the transforming matrix H is computed with RANSAC algorithm and LM algorithm. And
finally image mosaic is completed with smoothing algorithm. The method implements automatically and avoids the disadvantages of traditional image mosaic method under different scale and illumination conditions. Experimental results show that the image mosaic method is stable and effective. Platform: |
Size: 550912 |
Author:lingliu |
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Search - sift based method for image mosaic