基于这些旋转不变量给出了一种形状相似性度量。
A shape similarity measure is defined on the extracted rotation invariants.
它最初作为一种关键点的特征提出来的，其主要思想是在尺度空间寻找极值点，提取位置，尺度，旋转不变量；
The main idea is to find extreme value in the scale space, extracting location, scale and rotation invariant.
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.
这种表示是客体平移、旋转和相似变化的不变量。
This representation is invariant to the translation, rotation, and scaling change of the object.
寻找相对于平移、尺度、旋转、扭曲不变的仿射不变量是现今多尺度分析在模式识别中应用的关键性问题。
It's a key problem to search for affine invariant with respect to translation, scaling, rotation and skewing in multi-resolution analysis.
微分不变量具有平移和旋转不变性，并且对噪声具有较强的鲁棒性。
The differential invariants are robust to the noise and also invariant to the translation and rotation.
视觉不变量是指那些对于尺度变化、物体移动、旋转、放射、透视变化仍保持不变的特征。
Visual invariants are those changes in scale, moving, rotating, radiation, the perspective changes remain invariant feature.
视觉不变量是指那些对于尺度变化、物体移动、旋转、放射、透视变化仍保持不变的特征。
Visual invariants are those changes in scale, moving, rotating, radiation, the perspective changes remain invariant feature.
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