利用图像的不变矩特征进行目标识别是一种有效的方法。
It is an effective method to use the invariant moment features for target recognition.
视觉是人类最完善的感知系统，基于视觉不变量的平面目标识别方法近年来得到广泛的关注。
Vision is the best perception system of human. Vision invariants for planar object recognition catch our attention.
矩不变量在图像进行平移、旋转和尺度变换时保持定值，因此被广泛使用在目标识别、图像分类、图像压缩和场景匹配等各种领域。
The invariable moment, which is invariable to the translation, scaling and rotation of image, is widely used in object recognition, image classification, image condensation, scene matching and so on.
提出一种以目标检测、目标分割、目标方位角估计和目标不变性特征提取为线索的SAR目标识别框架。
We propose a multistage SAR target recognition process based on target detection, target segmentation, target aspect estimation and invariant feature extraction.
提出了一种基于几何不变性和BP网络的二维目标识别算法。
A 2d object recognition algorithm based on geometry invariant and BP Network.
为了识别空间目标与气球诱饵，提出了基于光谱角时序不变性的红外目标识别方法。
The infrared target recognition method based on the invariance of spectral Angle in time sequence is put forward in order to recognizing spatial target and balloon decoy.
为解决此类问题，本文将不变量理论应用于目标识别中，以解决因目标移动造成的失真问题。
In this article Invariant Theory is used in the image recognition to resolve the image distortions problems.
为解决此类问题，本文将不变量理论应用于目标识别中，以解决因目标移动造成的失真问题。
In this article Invariant Theory is used in the image recognition to resolve the image distortions problems.
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