CAJ | 학술논문

尺度不变特征变换（ SIFT）图像匹配算法采用高斯差分算子（ DoG）进行特征点检测，计算上使用相邻尺度高斯平滑后图像相减。在实践中，检测出的特征点遍布整个图像，造成后续计算量大且误配率高，降低了SIFT算法的实时性。针对以上问题，采用一种优化后的区域检测方法对SIFT特征点检测进行改进。首先利用优化后的区域检测方法检测出目标物体，然后运用DoG算子提取特征点，使特征点集中在目标物体上，从而简化计算，提高SIFT算法的实时性。最后，给出改进算法的实验结果和应用前景。
척도불변특정변환（ SIFT）도상필배산법채용고사차분산자（ DoG）진행특정점검측，계산상사용상린척도고사평활후도상상감。재실천중，검측출적특정점편포정개도상，조성후속계산량대차오배솔고，강저료SIFT산법적실시성。침대이상문제，채용일충우화후적구역검측방법대SIFT특정점검측진행개진。수선이용우화후적구역검측방법검측출목표물체，연후운용DoG산자제취특정점，사특정점집중재목표물체상，종이간화계산，제고SIFT산법적실시성。최후，급출개진산법적실험결과화응용전경。
Difference of Gaussians operator is used in SIFT image matching algorithm to detect feature points .In calculation the adjacent scales Gaussian smoothed image subtraction is used.In practices, the feature points detected are scattered on whole image and that leads to large amount of subsequent calculations and high mismatching rate , and the real-time property of SIFT algorithm is reduced.To solve the above problems, an optimised region detection method is adopted to improve the feature points detection of SIFT algorithm.First, the target object is detected by an optimised region detection method .Then, the feature points are extracted by Difference of Gaussians operator.It makes the feature points concentrated on the target object, so that simplifies the calculations and improves the real-time property of SIFT algorithm.Finally, the experimental results and application prospects of the improved algorithm are given.