CAJ | 학술논문

为了降低图像配准误匹配率以及减少 RANSAC 算法特征优化迭代次数，提出了 SIFT-FCACO 的图像配准算法，用快速收敛的蚁群算法对图像匹配后的特征点对进行优化。实验结果表明，该算法不仅减少了匹配时间，而且提高了匹配的准确率。
위료강저도상배준오필배솔이급감소 RANSAC 산법특정우화질대차수，제출료 SIFT-FCACO 적도상배준산법，용쾌속수렴적의군산법대도상필배후적특정점대진행우화。실험결과표명，해산법불부감소료필배시간，이차제고료필배적준학솔。
In order to improve the image registration error matching rate and reduce the RANSAC algorithm of feature optimization iterations, the image registration algorithm SIFT-FCACO is proposed, which uses image matching feature point pairs to optimize the ant colony algorithm with fast convergence. Experiment results show that this algorithm can reduce the matching time , and improves the matching accuracy.