Fast and accurate computation of Racah moment invariants for image classification

被引:30
作者
Benouini, Rachid [1 ]
Batioua, Imad [1 ]
Zenkouar, Khalid [1 ]
Zahi, Azeddine [1 ]
El Fadili, Hakim [2 ]
Qjidaa, Hassan [3 ]
机构
[1] Univ Sidi Mohamed Ben Abdellah, Fac Sci & Technol, Lab Intelligent Syst & Applicat LSIA, BP 2202,Route Immouzer, Fes 30003, Morocco
[2] Univ Sidi Mohamed Ben Abdellah, Ecole Natl Sci Appl Fez, Fes, Morocco
[3] Sidi Mohamed Ben Abdellah Univ, Fac Sci Dhar El Mehraz, LESSI, Fes, Morocco
关键词
Racah moment invariants; Racah polynomials; Fast algorithm; Accurate computation; Direct method; Recursive method; Image classification; Pattern recognition; PSEUDO-ZERNIKE MOMENTS; ORTHOGONAL POLYNOMIALS; TRANSLATION; ALGORITHMS; SCALE;
D O I
10.1016/j.patcog.2019.02.014
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, a new set of moment invariants, named Racah Moment Invariants (RMI), is introduced in the field of image analysis. This new set can be used to describe pattern feature independently of Rotation, Scaling and Translation transforms. Moreover, new fast and accurate algorithm, using recursive method, is developed for accelerating the computation time of the newly proposed invariants, as well as, for enhancing their numerical stability. Subsequently, several experiments have been performed. Initially, the numerical stability and computational cost are depicted. Secondly, the global and local features extraction are clearly illustrated. Then, invariability property and noise robustness are investigated. Finally, the discrimination power and the classification accuracy of the proposed invariants are extensively tested on several publicly available databases. The presented theoretical and experimental results, clearly show that the proposed method can be extremely useful in the fields of image classification. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页码:100 / 110
页数:11
相关论文
共 31 条
[1]  
Ananth J. P., 2012, P 4 INT C BIOINF BIO, V29, P218
[2]   SET OF ORTHOGONAL POLYNOMIALS THAT GENERALIZE THE RACAH COEFFICIENTS OR 6-J SYMBOLS [J].
ASKEY, R ;
WILSON, J .
SIAM JOURNAL ON MATHEMATICAL ANALYSIS, 1979, 10 (05) :1008-1016
[3]   Image analysis using new set of separable two-dimensional discrete orthogonal moments based on Racah polynomials [J].
Batioua, Imad ;
Benouini, Rachid ;
Zenkouar, Khalid ;
El Fadili, Hakim .
EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING, 2017,
[4]  
Benouini R, 2018, MULTIMED TOOLS APPL, P1
[5]   High-precision and fast computation of Jacobi-Fourier moments for image description [J].
Camacho-Bello, C. ;
Toxqui-Quitl, C. ;
Padilla-Vivanco, A. ;
Baez-Rojas, J. J. .
JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, 2014, 31 (01) :124-134
[6]  
Flusser J., 2016, 2D and 3D image analysis by moments, P1, DOI DOI 10.1002/9781119039402
[7]   TRANSLATION AND SCALE INVARIANTS OF HAHN MOMENTS [J].
Goh, Hock-Ann ;
Chong, Chee-Way ;
Besar, Rosli ;
Abas, Fazly Salleh ;
Sim, Kok-Swee .
INTERNATIONAL JOURNAL OF IMAGE AND GRAPHICS, 2009, 9 (02) :271-285
[8]   Naturally combined shape-color moment invariants under affine transformations [J].
Gong, Ming ;
Hao, You ;
Mo, Hanlin ;
Li, Hua .
COMPUTER VISION AND IMAGE UNDERSTANDING, 2017, 162 :46-56
[9]   Image representation using accurate orthogonal Gegenbauer moments [J].
Hosny, Khalid M. .
PATTERN RECOGNITION LETTERS, 2011, 32 (06) :795-804
[10]   VISUAL-PATTERN RECOGNITION BY MOMENT INVARIANTS [J].
HU, M .
IRE TRANSACTIONS ON INFORMATION THEORY, 1962, 8 (02) :179-&