Accurately and automatically detecting image orientation is a task of great importance in intelligent image processing. In this paper, we present automatic image orientation detection algorithms based on these features: color moments; harris corner; phase symmetry; edge direction histogram. The statistical learning support vector machines, AdaBoost, Subspace classifier are used in our approach ...

We present a comprehensive evaluation of performance of visual feature representations for MediaEval 2011 Violent Scenes Detection Task. As for global features, color moments, color histogram, edge orientation histogram, and local binary patterns are used. As for local features, keypoint detectors such as Harris Laplace, Hessian Laplace, Harris Affine, Dense Sampling are used to extract keypoin...

Though often not explicitly stated, the method of moments is one of the heavily used methods in queueing analysis. A typical, tagged customer is traced as it proceeds through the system and the components of its delay are individually analyzed. Using the moments of these components, moments of the sojourn and waiting times of an arbitrary customer can be derived. By this method, expected values...

Generalized Pareto distribution play an important role in reliability, extreme value theory, and other branches of applied probability and statistics. This family of distributions includes exponential distribution, Pareto distribution, and Power distribution. In this paper, we established exact expressions and recurrence relations satisfied by the quotient moments of generalized order statistic...

Received July 7, 1993; revised manuscript received November 22, 1993; accepted December 14, 1993 We propose orthogonal Fourier-Mellin moments, which are more suitable than Zernike moments, for scaleand rotation-invariant pattern recognition. The new orthogonal radial polynomials have more zeros than do the Zernike radial polynomials in the region of small radial distance. The orthogonal Fourier...

Zernike moments are complex moments with the orthogonal Zernike polynomials as kernel function, compared with other moments; Zernike moments have greater advantages in image rotation and low noise sensitivity. Because of the Zernike moments have image rotation invariance, and can construct arbitrary high order moments, it can be used for target recognition. In this paper, the Zernike moment alg...

Selecting appropriate feature extraction method is absolutely one of the most important factors to archive high classification performance in pattern recognition systems. Among different feature extraction methods proposed for pattern recognition, statistical moments seem to be so promising. Whereas theoretical comparison of the moments is too complicated, in this paper, an experimental evaluat...

Uncertain set theory is a generalization of uncertainty theory that has become a new branch of mathematics for modeling human belief degrees. Uncertain set is a fundamental concept to describe unsharp concepts in uncertain set theory. The moments are important characteristics of an uncertain set. This paper studies the moments and central moments of uncertain set and gives some formulas to calc...

The electrovacuum around a rotating massive body with electric charge density is described by its multipole moments (mass moments, mass-current moments, electric moments, and magnetic moments). A small uncharged test particle orbiting around such a body moves on geodesics if gravitational radiation is ignored. The waves emitted by the small body carry information about the geometry of the centr...

Moments of absorbing Markov chain are considered. First moments and non-mixed second moments are determined in classical textbooks such as the book of J. Kemeny and J. Snell “Finite Markov Chains”. The reason is that the first moments and the non-mixed second moments can be easily expressed in a matrix form. Since the representation of mixed moments of higher orders in a matrix form is not stra...