改进的自适应SUSAN角点特征提取方法
An improved self-adapting corner feature extraction method
陈洪,李进强
摘要(Abstract)：
针对目前大多数的角点特征提取算法存在算法结构过于复杂、运行效率偏低及可推广性偏差等方面的局限性,该文通过改进SUSAN算法中灰度差阈值的获取方法,提出一种自适应的角点特征提取方法。该方法首先采用高斯滤波对原始影像做预处理,然后利用Ly算子初步探测概略角点特征集合,最后利用改进的SUSAN角点检测算法从概略角点特征精确确定角点特征。实验结果表明,该方法提高了角点检测的精度,缩短了角点特征提取时间,具有较好的鲁棒性。
关键词(KeyWords)： 角点提取;自适应;SUSAN算法;高斯滤波
基金项目(Foundation):
作者(Author): 陈洪,李进强
DOI: 10.16251/j.cnki.1009-2307.2017.12.020
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