摘要
特征提取是数字图像处理和计算机视觉中的一项重要技术,而利用特征描述算子来构造图像特征点是图像特征提取及配准中的一个关键步骤。SIFT特征点检测算子具有平移、旋转及缩放不变性,在图像配准中应用很广泛。针对基于SIFT特征的64维描述算子的不足进行了改进。通过仿真实验证明,改进后的算法比原算法精度更高,且时间复杂度有所降低。
Feature extraction is an important technology in digital image processing and computer vision. And making use of feature descriptor to construct the image feature point is a crucial step in the image feature extraction and image registration. SIFT feature point detection operator has the advantages of translation, rotation and scaling invariance. So, it is widely used in image registration. We mainly improved the 64 dimensional description operator based on the SIFT characteristics. The simulation results prove that the improved algorithm has higher accuracy than the original algo- rithm,and the time complexity is reduced.
出处
《计算机科学》
CSCD
北大核心
2013年第7期270-272,共3页
Computer Science
基金
国家自然科学基金(610-71118)
重庆邮电大学自然科学基金(A2009-62)资助
关键词
特征提取
特征点
SIFT
图像配准
Feature extraction,Feature point,SIFT, Image registration
