王凌云,尹海波,王琪.SURF和RANSAC在图像拼接中的应用[J].电子测量技术,2016,39(4):71-75
SURF和RANSAC在图像拼接中的应用
Application of SURF and RANSAC algorithm on image stitching
  
DOI:
中文关键词:  图像拼接  快速鲁棒描述子(SURF)  随机采样一致(RANSAC)
英文关键词:image stitching  Speed Up Robust Feature (SURF)  Random Sample Consensus(RANSAC)
基金项目:
作者单位
王凌云 长春理工大学 仪器科学与技术长春130022 
尹海波 长春理工大学 仪器科学与技术长春130022 
王琪 长春理工大学 仪器科学与技术长春130022 
AuthorInstitution
Wang Lingyun The ChangChun Univercity of Science and Technology,Department of Instrument Science and Technology, Changchun 130022,China 
Yin Haibo The ChangChun Univercity of Science and Technology,Department of Instrument Science and Technology, Changchun 130022,China 
Wang Qi The ChangChun Univercity of Science and Technology,Department of Instrument Science and Technology, Changchun 130022,China 
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中文摘要:
      图像特征检测在计算机视觉带动下得到了快速发展。SURF特征描述能够非常稳定快速地对图像特征进行检测和描述。RANSAC能够在inliers大于50%的条件下很好地估计出模型参数,在特征点匹配上起到了关键作用。本文利用SURF特征描述子对图像特征点进行检测和描述,然后运用交叉匹配的策略有效地消除一些错误匹配点对,然后运用RANSAC算法进行模型估计,最后使用线性加权的方式对图像进行融合。该方法利用了SURF快速检测和稳定性的特点和RANSAC算法时间复杂度小的特点进行特征点快速准确匹配,最终能够实现快速的图像拼接。
英文摘要:
      Image feature detection has been developed rapidly in the computer vision, and the SURF feature description can be very stable and fast. RANSAC can estimate the parameters of the model under the condition that the inliers is more than 50%, and it plays a key role in the feature points matching. The surf descriptor of image feature points of detection and description, and then applying the cross matching strategy effectively eliminate wrong matching points, then the use of RANSAC algorithm to estimate the model. Finally, using the linear weighted method for image fusion. This method can be used to match images in low time complexity with the the SURF feature detector and descriptor and RANSAC algorithm.
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