摘要 :
Orthogonal moments provide an efficient mathematical framework for computer vision, image analysis, and pattern recognition. They are derived from the polynomials that are relatively perpendicular to each other. Orthogonal moments...
展开
Orthogonal moments provide an efficient mathematical framework for computer vision, image analysis, and pattern recognition. They are derived from the polynomials that are relatively perpendicular to each other. Orthogonal moments are more efficient than non-orthogonal moments for image representation with minimum attribute redundancy, robustness to noise, invariance to rotation, translation, and scaling. Orthogonal moments can be both continuous and discrete. Prominent continuous moments are Zernike, Pseudo-Zernike, Legendre, and Gaussian-Hermite. This article provides a comprehensive and comparative review for continuous orthogonal moments along with their applications.
收起
摘要 :
'Invalid moment sets'-sets of quantities nominally moments but for which no underlying distribution could exist and therefore not moment sets-are generated in Eulerian models from valid sets by independent advection of each moment...
展开
'Invalid moment sets'-sets of quantities nominally moments but for which no underlying distribution could exist and therefore not moment sets-are generated in Eulerian models from valid sets by independent advection of each moment.Examination of invalid set generation by two representative advection schemes in one dimension for ensembles of 10 test cases spanning a range of initial moment sets and flow velocities reveals invalid set frequencies >=0.7% for both schemes.Standard moment methods cannot accommodate invalid sets.Solutions to this problem are presented and evaluated for the ensembles and accurate moment advection free of invalid sets was obtained for both schemes.A new closure scheme insensitive to invalid sets using Lagrange interpolation of moment equation kernels is described and evaluated for condensation,dry deposition,and gravitational settling and found to match the high accuracy of quadrature.
收起
摘要 :
In this research, we have developed a new algorithm to compute the moments defined in a rectangular region. By applying the recurrent formulas, symmetry properties, and particularly the parallelized matrix operations, our proposed...
展开
In this research, we have developed a new algorithm to compute the moments defined in a rectangular region. By applying the recurrent formulas, symmetry properties, and particularly the parallelized matrix operations, our proposed computational method can improve the efficiency of computing Legendre, Gegenbauer, and Jacobi moments extensively with highly satisfied accuracy. To verify this new computational algorithm, the image reconstructions from the higher orders of Legendre, Gegenbauer, and Jacobi moments are performed on a testing image sized at 1024 x 1024 with very encouraging results. It took only a few seconds to compute moments and conduct the image reconstructions from the 1000-th order of the Legendre, Gegenbauer, and Jacobi moments with the PSNR values up to 45. By utilizing our new algorithm, image analysis and recognition applications using the higher orders of moments defined in a rectangular region in the range of milliseconds will be possible. (C) 2019 Elsevier Ltd. All rights reserved.
收起
摘要 :
Moment functions are widely use in image analysis as feature descriptors for pattern recognition. In this work, we propose a method to recognition problem using Legendre moments. The proposed approach is based on the decomposition...
展开
Moment functions are widely use in image analysis as feature descriptors for pattern recognition. In this work, we propose a method to recognition problem using Legendre moments. The proposed approach is based on the decomposition of the original image into block images. The optimal number of moment used to represent original image is deduced from the measure of the error between the original image and its reconstructed. Servo image is used to demonstrate the performance of the proposed method.
收起
摘要 :
Those of a certain age will remember a seminal moment in the film The Graduate when the young and aimless Benjamin Braddock (Dustin Hoffman) is taken aside at his graduation party by Mr McGuire, who wants to provide him with just ...
展开
Those of a certain age will remember a seminal moment in the film The Graduate when the young and aimless Benjamin Braddock (Dustin Hoffman) is taken aside at his graduation party by Mr McGuire, who wants to provide him with just one word of unsolicited career advice. 'Plastics,' McGuire enthuses. And by way of explanation for the dumbfounded Hoffman, he adds, 'There's a great future in plastics.'
收起
摘要 :
The aim of the present comment is to point out wrong claim made by (Hosny, 2010) on the exact computation of radial moments. These errors are corrected in the comment. It is shown that the correct values of radial moments can be c...
展开
The aim of the present comment is to point out wrong claim made by (Hosny, 2010) on the exact computation of radial moments. These errors are corrected in the comment. It is shown that the correct values of radial moments can be computed from numerical integration as exact computation of radial moments is not possible when the difference between moment order and repetition is odd.
收起
摘要 :
The increasing interest in processing sequences of images motivates development of techniques for sequence-based object analysis and description. Accordingly, new velocity moments have been developed to allow a statistical descrip...
展开
The increasing interest in processing sequences of images motivates development of techniques for sequence-based object analysis and description. Accordingly, new velocity moments have been developed to allow a statistical description of both shape and associated motion through an image sequence. Through a generic framework motion information is determined using the established centralised moments, enabling statistical moments to be applied to motion based time series analysis. The translation invariant Cartesian velocity moments suffer from highly correlated descriptions due to their non-orthogonality. The new Zernike velocity moments overcome this by using orthogonal spatial descriptions through the proven orthogonal Zernike basis. Further, they are translation and scale invariant. To illustrate their benefits and application the Zernike velocity moments have been applied to gait recognition—an emergent biometric. Good recognition results have been achieved on multiple datasets using relatively few spatial and/or motion features and basic feature selection and classification techniques. The prime aim of this new technique is to allow the generation of statistical features which encode shape and motion information, with generic application capability. Applied performance analyses illustrate the properties of the Zernike velocity moments which exploit temporal correlation to improve a shape's description. It is demonstrated how the temporal correlation improves the performance of the descriptor under more generalised application scenarios, including reduced resolution imagery and occlusion.
收起
摘要 :
Existence and construction of the solutions of some Markov moment problems are discussed. Starting fromthe moments of a solution, one recalls a method of recovering this solution, also solving approximatelyrelated systems with inf...
展开
Existence and construction of the solutions of some Markov moment problems are discussed. Starting fromthe moments of a solution, one recalls a method of recovering this solution, also solving approximatelyrelated systems with infinite many nonlinear equations and infinite unknowns. This is the first aim of thisreview paper. Extension of linear forms with two constraints is applied. Measure theory arguments play acentral role. Other results in analysis and functional analysis are used tacitly, sending the reader to thereferences for unproved stated theorems. Secondly, in the end, existence of solutions of special Markovmoment problems is studied.
收起
摘要 :
Iris recognition under less constrained environment poses a challenge to be considered for high-security applications. In this paper, discrete orthogonal moment-based features including Tchebichef, Krawtchouk and Dual-Hahn are pro...
展开
Iris recognition under less constrained environment poses a challenge to be considered for high-security applications. In this paper, discrete orthogonal moment-based features including Tchebichef, Krawtchouk and Dual-Hahn are proposed which prove to be effective for both near-infrared and visible images. The local as well as global features are extracted from localized iris regions till 15th order with invariance (scale, rotation, translation and illumination) properties and tolerance to noise. The performance of the moment-based features is evaluated on four publicly available databases: CASIA-IrisV4-Interval, IITD.v1, UPOL and UBIRIS.v2. It is found that the proposed method gives encouraging results in terms of accuracy, equal error rate and decidability index as compared to the competing techniques available in the literature.
收起
摘要 :
This paper deals with moment invariants with respect to image blurring. It is mainly a reaction to the works of Zhang and Chen , recently published in these Transactions. We present a general method on how to construct blur invar...
展开
This paper deals with moment invariants with respect to image blurring. It is mainly a reaction to the works of Zhang and Chen , recently published in these Transactions. We present a general method on how to construct blur invariants from arbitrary moments and show that it is no longer necessary to separately derive the invariants for each polynomial basis. We show how to discard dependent terms in blur invariants definition and discuss a proper implementation of the invariants in orthogonal bases using recurrent relations. An example for Legendre moments is given.
收起
原文获取