Image representation is an important topic in computer vision and pattern recognition. It
plays a fundamental role in a range of applications toward understanding visual contents …

In order to reduce the time complexity and improve the reconstruction performance of
traditional method for Radial Harmonic Fourier Moments (RHFMs), we introduce a fast and …

In this paper, we propose a new set of orthogonal moments based on Exponent functions,
named Exponent-Fourier moments (EFMs), which are suitable for image analysis and …

In the process of network transmission, medical images are maliciously attacked to cause
the loss of diagnostic data or the leakage of patient privacy. To solve this problem, this paper …

Image moments have attracted extensive attention from researchers because of their good
global feature description ability and geometric invariance. In recent years, with the wide …

A novel kernel-based method is proposed for fast, highly accurate and numerically stable
computations of polar harmonic transforms (PHT) in polar coordinates. Euler formula is used …

Abstract The Jacobi-Fourier moments (JFMs) provide a wide class of orthogonal rotation
invariant moments (ORIMs) which are useful for many image processing, pattern recognition …

The convolutional layers of the standard convolutional neural networks (CNNs) are
equivariant to translation. Recently, a new class of CNNs is introduced which is equivariant …

The wavelet moments are very useful image descriptors which contain both global and local
characteristics of an image. Its usefulness is further characterized by rotation invariant …

A novel method is proposed for highly accurate, fast and numerically stable computation of
the higher order Quaternion Polar Complex Exponential Transform (QPCET) moments for …