摘要
提出一种基于各向异性高斯方向导数滤波器提取图像粗轮廓检测角点的方法。首先利用多方向的各向异性高斯方向导数滤波器提取图像多方向的灰度变化信息,然后利用像素间梯度相关性提取图像粗轮廓。最后在提取的图像粗轮廓的基础上构造自相关矩阵并求解其特征值,利用特征值归一化的乘积做为角点的测度。实验证明本算法具有噪声鲁棒性及角点定位准确性。
This paper presents proposes a corner detector method based on anisotropic Gaussian directional derivative filters to extract the crude outline of image.Firstly,multi-direction anisotropic Gaussian directional derivative filters are used to extract the variation of gray change information,and then the crude outline is extracted by using the gradient correlation of pixels.Finally,we construct the auto-correlation matrix on the basis of the extracted crude outline and normalize eigenvalues of the auto-correlation matrix,then the product of normalized eigenvalues is served as the measure of corner extracting.Experiments show that the algorithm is noise-robust and location-accurate.
出处
《电子测量技术》
2015年第8期69-72,共4页
Electronic Measurement Technology
基金
国家自然科学基金资助项目(61401347)
关键词
角点检测
各向异性高斯方向导数滤波器
梯度相关性
粗轮廓
自相关矩阵
corner detection
anisotropic Gaussian directional derivative filters
gradient correlation
crude outline
auto-correlation matrix