计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2014年
2期
189-193
,共5页
尺度不变特征变换(SIFT)特征点匹配%图像配准%欧氏距离%双阈值
呎度不變特徵變換(SIFT)特徵點匹配%圖像配準%歐氏距離%雙閾值
척도불변특정변환(SIFT)특정점필배%도상배준%구씨거리%쌍역치
Scale Invariant Feature Transform(SIFT) feature point matching%image registration%Euclidean distance%double threshold
针对SIFT匹配算法和SIFT与RANSAC结合的匹配算法都存在不同程度误匹配的问题，提出一种基于局部SIFT特征点的双阈值匹配算法。设计变步长迭代准则获取SIFT双阈值，其中大阈值匹配获得一组稀疏的精确匹配，小阈值匹配获得一组可能存在误匹配的密集匹配。以精确匹配建立目标的形变约束模型，以此为基础从密集匹配中删除误匹配。通过这些正确的匹配点估计两幅图像之间的变换矩阵。为了降低算法所需时间，提高效率，通过分析图像的纹理变化，采用提取其变化最为剧烈的区域来代表整幅图像进行匹配运算。实验结果表明，该算法在图像存在平移、旋转等仿射变化情况下具有配准精度高，稳定和快速等特点。
針對SIFT匹配算法和SIFT與RANSAC結閤的匹配算法都存在不同程度誤匹配的問題，提齣一種基于跼部SIFT特徵點的雙閾值匹配算法。設計變步長迭代準則穫取SIFT雙閾值，其中大閾值匹配穫得一組稀疏的精確匹配，小閾值匹配穫得一組可能存在誤匹配的密集匹配。以精確匹配建立目標的形變約束模型，以此為基礎從密集匹配中刪除誤匹配。通過這些正確的匹配點估計兩幅圖像之間的變換矩陣。為瞭降低算法所需時間，提高效率，通過分析圖像的紋理變化，採用提取其變化最為劇烈的區域來代錶整幅圖像進行匹配運算。實驗結果錶明，該算法在圖像存在平移、鏇轉等倣射變化情況下具有配準精度高，穩定和快速等特點。
침대SIFT필배산법화SIFT여RANSAC결합적필배산법도존재불동정도오필배적문제，제출일충기우국부SIFT특정점적쌍역치필배산법。설계변보장질대준칙획취SIFT쌍역치，기중대역치필배획득일조희소적정학필배，소역치필배획득일조가능존재오필배적밀집필배。이정학필배건립목표적형변약속모형，이차위기출종밀집필배중산제오필배。통과저사정학적필배점고계량폭도상지간적변환구진。위료강저산법소수시간，제고효솔，통과분석도상적문리변화，채용제취기변화최위극렬적구역래대표정폭도상진행필배운산。실험결과표명，해산법재도상존재평이、선전등방사변화정황하구유배준정도고，은정화쾌속등특점。
Since the SIFT matching algorithm and the SIFT combined with the RANSAC matching algorithm both exist the mismatching problem in varies degree, a double threshold matching algorithm based on local SIFT feature points is proposed. This paper designs the iteration criteria of the variable step size to obtain the double threshold of the SIFT, where the large threshold matching obtains a set of sparse precision matching, and the small threshold matching obtains a set of intensive matching in which mismatching may exists. Then the deformation constraint model is established based on the precise matching, which is the basis of removing the mismatching from the intensive matching. The transformation matrix is estimated by these correct matching points between the two images. To reduce the required time and increase efficiency of the algorithm, the most sharply changing region is extracted by analysing the changes of the image texture, which represents the whole image to do the matching operation. The experimental results indicate that the proposed matching algorithm has advantages of high accuracy, stability and rapidity in the situation that the affine changes of translation, rota-tion etc exist in the images.
