Moment invariants are well-established and effective shape descriptors for image classification. In this report, we introduce a package for R-language, named IM, that implements the calculation of moments for images and allows the reconstruction of images from moments within an object-oriented framework. Several types of moments may be computed using the IM library, including discrete and continuous Chebyshev, Gegenbauer, Legendre, Krawtchouk, dual Hahn, generalized pseudo-Zernike, Fourier-Mellin, and radial harmonic Fourier moments. In addition, custom bivariate types of moments can be calculated using combinations of two different types of polynomials. A method of polar transformation of pixel coordinates is used to provide an approximate invariance to rotation for moments that are orthogonal over a rectangle. The different types of polynomials used to calculate moments are discussed in this report, as well as comparisons of reconstruction and running time. Examples of image classification using image moments are provided.
翻译:动因是图像分类的固定和有效的形状描述符。 在本报告中, 我们为 R 语言引入了一个名为 IM 的包件, 用于计算图像的瞬间, 并允许在目标导向框架内从瞬间重建图像。 几种瞬间可以使用 IM 库来计算, 包括离散和连续的 Chebyshev、 Gegenbauer、 Lultre、 Krawtchouk、 双 Hahn、 通用伪Zernike、 Fourier- Mellin 和 反射调 Fourier 时。 此外, 可以使用两种不同类型多数值的组合组合来计算自定义的两变时间类型 。 一种对像素坐标的极变方法, 用来提供在矩形上旋转时的近似变量 。 本报告讨论了用于计算时段的不同类型, 以及重建和运行时间的比较。 提供了使用图像时刻进行图像分类的示例 。