计算机科学 ›› 2017, Vol. 44 ›› Issue (Z6): 157-160.doi: 10.11896/j.issn.1002-137X.2017.6A.036
刘川熙,赵汝进,刘恩海,洪裕珍
LIU Chuan-xi, ZHAO Ru-jin, LIU En-hai and HONG Yu-zhen
摘要: 针对基于欧氏距离比值作为图像尺度不变特征变换(SIFT)特征匹配相似性度量时,距离比阈值难以设置最优,且固定距离比阈值易引起误匹配或漏匹配等问题,引入随机抽样一致性(RANSAC)算法。该算法对SIFT匹配算法中的距离比阈值进行自适应优化,确定最佳的阈值,再利用双向匹配的方法剔除误匹配点。实验结果表明,针对不同的实验图像,所提算法都能自适应地求解出一个最优的比例阈值,使得匹配点数最多,同时具有较高的匹配正确率,经过双向匹配的策略优化后效果更好。
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