计算机科学 ›› 2016, Vol. 43 ›› Issue (9): 289-294.doi: 10.11896/j.issn.1002-137X.2016.09.058
周来恩,王晓丹
ZHOU Lai-en and WANG Xiao-dan
摘要： 由于兴趣点是图像中的基础、关键特征,因此兴趣点检测是图像配准、图像检索以及图像识别的关键步骤。基于兴趣点对于图像特征响应较为强烈的特性,结合非监督特征学习算法可以自主地从无标签的样本中提取特征的思想,提出了UFL-ID兴趣点检测算法。该算法无监督学习了图像的底层特征,对特征进行信息量和各向同性的评价,并利用特征的卷积响应及评价参数寻找图像中的兴趣点。与其他常见的兴趣点检测算法的对比实验表明,该算法具有良好的重复性与抗噪能力。
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