Existing works on orthogonal moments are mainly focused on optimizing classical orthogonal Cartesian moments, such as Legendre moments, Gauss-Hermite moments, Gegenbauer moments, and Chebyshev moments. Research in this area generally includes accurate calculation, fast computation, robustness/invariance optimization, and the application of orthogonal moments. This paper presents the inclusion of the integration method proposed by Holoborodko to calculate the Legendre moments. The results obtained are compared with the traditional equation and the methods proposed by Hosny and Pawlak to approximate the integration computation
Orthogonal moments play an important role in image analysis and other similar applications. However,...
Various types of moments have been used to recognize image patterns in a number of applications. The...
Discrete orthogonal moments are powerful tools for characterizing image shape features for applicati...
Image feature representation techniques using orthogonal moment functions have been used in many app...
Several pattern recognition applications use orthogonal moments to capture independent shape charac...
Abstract − Several pattern recognition applications use orthogonal moments to capture independent sh...
Abstract: In this research, a numerical integration method is proposed to improve the computational ...
Abstract—Legendre moments are continuous moments, hence, when applied to discrete-space images, nume...
A multi-distorted invariant orthogonal moments, Jacobi-Fourier Moments (JFM), were proposed. The int...
Legendre orthogonal moments have been widely used in the field of image analysis. Because their comp...
This paper presents recursive algorithms for fast computation of Legendre and Zernike moments of a g...
Statistical moments can offer a powerful means for object description in object sequences. Moments u...
International audienceA new set, to our knowledge, of orthogonal moment functions for describing ima...
International audienceThe several moment families have been reviewed in a first paper [1]. A classif...
The final publication is available at link.springer.comAn image can be seen as an element of a vecto...
Orthogonal moments play an important role in image analysis and other similar applications. However,...
Various types of moments have been used to recognize image patterns in a number of applications. The...
Discrete orthogonal moments are powerful tools for characterizing image shape features for applicati...
Image feature representation techniques using orthogonal moment functions have been used in many app...
Several pattern recognition applications use orthogonal moments to capture independent shape charac...
Abstract − Several pattern recognition applications use orthogonal moments to capture independent sh...
Abstract: In this research, a numerical integration method is proposed to improve the computational ...
Abstract—Legendre moments are continuous moments, hence, when applied to discrete-space images, nume...
A multi-distorted invariant orthogonal moments, Jacobi-Fourier Moments (JFM), were proposed. The int...
Legendre orthogonal moments have been widely used in the field of image analysis. Because their comp...
This paper presents recursive algorithms for fast computation of Legendre and Zernike moments of a g...
Statistical moments can offer a powerful means for object description in object sequences. Moments u...
International audienceA new set, to our knowledge, of orthogonal moment functions for describing ima...
International audienceThe several moment families have been reviewed in a first paper [1]. A classif...
The final publication is available at link.springer.comAn image can be seen as an element of a vecto...
Orthogonal moments play an important role in image analysis and other similar applications. However,...
Various types of moments have been used to recognize image patterns in a number of applications. The...
Discrete orthogonal moments are powerful tools for characterizing image shape features for applicati...