Comparison of Image Patches Using Local Moment Invariants
Comparison of Image Patches Using Local Moment Invariants
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DOI：
10.1109/tip.2014.2315923
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发表时间：
2014-04
影响因子：
10.6
通讯作者：
Atilla Sit;Daisuke Kihara
中科院分区：
文献类型：
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作者：
Atilla Sit;Daisuke Kihara
我们提出了一组基于 Krawtchouk 多项式的新矩不变量，用于比较 2D 图像中的局部补丁。这些矩是根据离散函数计算得出的，不会因离散化而带来误差。与许多通常捕获全局特征的正交矩不同，Krawtchouk 矩可用于计算图像中感兴趣区域的局部描述符。这可以通过改变两个参数来实现，从而水平或垂直或两者都移动感兴趣区域的中心。此属性可以比较两个任意局部区域。我们证明，Krawtchouk 矩可以写成几何矩的线性组合，因此很容易转换为旋转、尺寸和位置无关的不变量。我们还使用 Hu 不变量构建基于 Hu 的局部不变量，并将它们用于由 Krawtchouk 多项式定义中给出的权重函数定位的图像。我们给出了基于 Krawtchouk 和 Hu 的局部不变量的公式，并评估了它们在人工生成的测试图像的局部比较中的判别性能。
We propose a new set of moment invariants based on Krawtchouk polynomials for comparison of local patches in 2D images. Being computed from discrete functions, these moments do not carry the error due to discretization. Unlike many orthogonal moments, which usually capture global features, Krawtchouk moments can be used to compute local descriptors from a region-of-interest in an image. This can be achieved by changing two parameters, and hence shifting the center of interest region horizontally or vertically or both. This property enables comparison of two arbitrary local regions. We show that Krawtchouk moments can be written as a linear combination of geometric moments, so easily converted to rotation, size, and position independent invariants. We also construct local Hu-based invariants using Hu invariants and utilizing them on images localized by the weight function given in the definition of Krawtchouk polynomials. We give the formulation of local Krawtchouk-based and Hu-based invariants, and evaluate their discriminative performance on local comparison of artificially generated test images.