Multi-scale image analysis for detection of characteristic component figure shapes and sizes
Multi-scale image analysis for detection of characteristic component figure shapes and sizes
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用于检测特征部件形状和尺寸的多尺度图像分析
DOI：
10.1109/icpr.1998.711983
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发表时间：
1998
期刊：
影响因子：
--
通讯作者：
K. Deguchi
中科院分区：
文献类型：
--
作者：
H. Hontani;K. Deguchi
提出了一种检测图像结构的特征形状和尺寸的方法。该方法首先通过不同尺度的高斯滤波器模糊图像。然后，在每个尺度上，计算每个位置的图像灰度轮廓的主曲率。随着比例的变化，主曲率也会发生变化。我们通过表征主曲率变化的类型来检测图像结构的固有形状和大小。为了进行检测，我们引入了由两个主曲率跨越的主曲率平面作为其笛卡尔坐标的思想。
A method which detects the characteristic shapes and sizes of image structures is proposed. The method first blurs an image by Gaussian filters with various scales. Then, at every scale, principal curvatures of the image gray-level profile are calculated for every position. As the scale changes, the principal curvatures change. We detect the inherent shapes and sizes of the image structures by characterizing the type of the change of the principal curvatures. For the detection, we introduce the idea of principal curvature plane spanned by the two principal curvatures as its Cartesian coordinates.