若把二值图或灰度图看作是二维密度分布函数，就可把矩技术应用于图像分析中。
The use of moments for image analysis is straightforward if we consider a binary or gray level image segment as a two-dimensional density distribution function.
本文提出了一种新的对于灰度图像的几何矩的快速算法。
The paper proposes a novel approach to calculate geometric moment for gray level image.
第四章分析了图像视觉特征的邻域矩特征描述，并对邻域矩特征进行自适应聚类提取边界和图像目标的视同灰度的提取。
In the fourth chapter the analysis for the visual features, the adaptive clustering and the extraction of the image area with the image similar visual brightness are analyzed.
由于局域波时频谱可以表示为灰度图像。因此，利用图像信息的不变矩进行故障特征提取。
Because the Local wave T-F spectrum can be showed in the gray image, so we use the moment invariants of time-frequency image as the fault features.
它是基于图象分割前后矩保持不变的原理，利用图象的灰度级直方图自动地确定多个分割阈值，该算法简单、计算量小。
It is based on the principle that the moment remains unchanged before and after the segmentation. This algorithm features simplicity and less calculation requirement.
本文主要研究了灰度互相关匹配算法、基于一维投影的匹配算法、基于直方图不变矩的匹配算法，分析并比较了各算法的优缺点。
In this method, some techniques are analyzed and adopted such as correlation algorithm, algorithm based on projection and algorithm based on invariant moments of histogram.
本文主要研究了灰度互相关匹配算法、基于一维投影的匹配算法、基于直方图不变矩的匹配算法，分析并比较了各算法的优缺点。
In this method, some techniques are analyzed and adopted such as correlation algorithm, algorithm based on projection and algorithm based on invariant moments of histogram.
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