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translation invariant相关的网络例句

查询词典 translation invariant

与 translation invariant 相关的网络例句 [注:此内容来源于网络,仅供参考]

To extract shaft orbit\'s features invariant to rotation, scaling and translation, the unique strengths of Haar orthogonal matrix type are found, the horizontal and vertical coordinates of shaft orbit are fast proceeded by Haar transform, respectively, and the slopes with different resolutions are obtained at different positions by using the corresponding transform coefficients, and then the multi-resolution angles between the adjacent slope straight line are extracted skillfully and used for the hierarchical recognition, the recognition process accords with the principle of human\'s recognizing things by using hierarchy analysis approach.

为提取轴心轨迹平移、旋转、尺度不变性特征,本文挖掘出Haar正交矩阵在图形识别中的独特优点,引入Haar正交矩阵分别对轴心轨迹的横、纵坐标进行快速变换,并利用变换后的对应系数得到轴心轨迹不同位置不同分辨率下的斜率,继而推求出相邻斜率直线之间的多分辨率夹角,所获夹角用于轴心轨迹的分层识别,其识别过程符合人类识别事物层次分析的规律。

In affine invariant space, the 3D object is not affected by geometric transformations, such as translation, rotation and scaling.

由于在仿射不变空间下,3D物体模型不受平移、旋转和比例变换的影响,故该水印方案对于此类变化具有很强的鲁棒性。

The feature has invariant character for translation, rotation and scale, and some degree of tolerance for affine transformation.

此特征不但具有二维的平移、旋转和尺度不变性,同时对由仿射变换引起的形变也具有一定容忍度。

RAHD is invariant to translation,scale, and rotation and the retrieved shapes are very perceptually acceptable due to the capturing of shape features in both radial and angular directions in spatial domain.

虽然目前文献上有很多种图像形状描述子,但是可以归分为两大类:基于轮廓的形状描述子和基于区域的形状描述子。

This paper analyses the influence of scale factor on moment invariant features in discrete,constructs a new moment invariant with both scale,translation and rotating invariance.

分析了在离散状态下比例因子对不变矩特征的影响,构造了一种新的不变矩,使其具有平移、旋转和比例因子的不变性。

Experimental results on the trademark image database show that the extracted features can describe the image shape better,and have good invariant property under translation,scale and rotation.

实验结果表明,距离分布信息熵能有效地刻画出二值图象的形状特征,并且具有良好的平移、旋转及尺度不变性,检索结果符合人眼的视觉感受。

At first, some properties in the sampling subspace are classified. Then, that the subspace spanned by the translation of a function is also a subspace is proved in the shift invariant subspace.

首先通过Zak变换刻画了抽样空间的一些性质,然后证明了在一个平移不变的抽样空间中,由其中任一个函数的整平移所张成的子空间也是抽样空间。

The classifier is invariant to rotation and translation and it is simple with less computation and easy to realize.

该方法对指纹的平移和旋转具有无关性,计算量小,易于实现。

The basic idea is to get the compacting shape first which is invariant to translation and scaling distortion by using Leu's shape compacting algorithm.

这种基本思想是首先得到压缩图形,这种图像是通过使用Leu图像压缩算法得到的,与平移和缩放扭曲无关的。

A large number of relaxation schemes for feature mapping, claimed to be invariant to transformation, have been reported. However, most of them can deal with transfor-mations involving only rotation and translation, but not scaling. To stay away from the issue of scaling, unrealistic assumptions have to be imposed, such as the conjectures that range data are available so that objects can be rescaled before mapping, and that object shapes are complete so that ratios between object shapes and prototypes can be figured out beforehand. In this paper, we propose a relaxation scheme which is able to be in-variant at a time to rotation, translation, as well as scaling.

截至目前为止已有不少供几何特徵匹配用之松弛法架构被提出来,这些架构虽然宣称可以对空间转移具有不变性,但是实际上,大部分只能处理和旋转及平移有关的转移,对於具有尺度因素的转换泽尽量避免,因此,便有各种不同的假设被加诸於所考虑的问题,例如假设我们已知景深值,因此可以先将物件的尺度正规化后再比对,或者假设物形式晚整的,於是物形和模型间的尺度比率事先可以推知。

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