1) projection moment invariant
投影不变矩
1.
Recognition of character strings based on projection moment invariant;
基于旋转投影不变矩的字符串识别方法
2) projective invariant
投影不变量
1.
An object tracking algorithm based on planar projective invariants is proposed,in which the values of invariants for object modeling and tracking are calculated with lines extracted from images.
提出了一种基于平面投影不变量的目标跟踪算法。
2.
The cross ratio of volume elements is shown as projective invariant after the spatial projective transformation is properly introduced.
从引入空间投影变换的概念入手，证明了体积之交比为一般的投影不变量，从而将其作为描述物体的度量。
3.
Projective invariants are independent of viewpoints, intrinsic and extrinsic camera parameters and common used in computer vision gradually.
投影不变量具有与视点和摄像机内外参数无关等优点 ,正逐渐成为计算机视觉研究的常用工具。
3) projective invariants
投影不变量
1.
The proposed method of recovering field of view lines by using projective invariants does not rely on the object movement in the scene and does not require information about camera parameters.
根据投影不变量FOV线生成法,在生成视野边界线时不依赖于场景中目标的运动,并且不需要摄像机参数的信息。
2.
Recently,projective invariants method is used to handoff object,but it will make mistakes in the case of multiple objects appear closely.
近年来,出现了利用投影不变量,计算目标在相邻摄像机中的投影位置来进行目标交接的方法,取得较好效果。
4) Projective/permutation invariant
投影置换不变量
5) local invariable projection
局部不变投影
6) Projection matrix
投影矩阵
1.
The acquisition of multiple vectors for the projection matrix simultaneous by geometry symmetry, and the real-time acquisition of the vector of the projection matrix are adopted to shorten acquiring time and save the memory space of projection matrix.
迭代成像中投影矩阵的获取速度直接影响算法的效率。
2.
We select the special relaxation parameter and put the projection matrix into many blocks according to the projection angles in the reconstruction procedure.
在重建过程中采取对投影矩阵按投影角度分块的方法,选取特定的松弛参数。
3.
A projection matrix method is presented in order to reduce the effect.
文中提出的投影矩阵方法首先在时域将主瓣杂波滤除,然后进行多普勒滤波,由于主瓣杂波被有效抑制,系统对慢速目标的检测能力大大提高。
补充资料：滤波反投影或卷积反投影
滤波反投影或卷积反投影
影像学术语。当代影像学设备进行影像重建的数学方法。在直接用扫描后所获得的投影轨迹剖面图反投影重建出的CT图像中，无法避免角度卷入条纹伪影(angular aliasing streaks)造成的模糊和失真。这种现象与被扫描层面的空间频率中高频信息的损失有关。使用一种精密的数学方法去除这种模糊。称为“展现”(unfolding)或去卷积(deconvolution)，即在反投影前使用一种数学的“滤器”或卷积函数对原始数据进行修正，然后再进行反投影。两步数学处理过程合称为滤波(修正后)反投影或卷积(后)反投影。这种方法的优点是处理过程简单，速度快，所得图像逼真、清晰。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条