Image retrieval and classication using shifted. Legendre invariant moments and Radial Basis Functions Neural Networks

被引：6
|
作者：
Hjouji, A. [1 ]
EL-Mekkaoui, J. [2 ]
Jourhmane, M. [1 ]
Qjidaa, H. [3 ]
Bouikhalene, B. [2 ]
机构：
[1] Sultan Moulay Slimane Univ, Fac Sci & Technol, Beni Mellal, Morocco
[2] Sultan Moulay Slimane Univ, Polydisciplinary Fac, Beni Mellal, Morocco
[3] Sidi Mohammed Ben Abdellah Univ, Fes, Morocco
来源：
SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING IN DATA SCIENCES (ICDS2018) | 2019年 / 148卷
关键词：
Shitted tcgcndre orthogonal polynoinials; shifted tcgcndre orthogonal invariant inoinents; Image Retrieval; Image classification; Radial Basis functions Neural Networks (RBF); ROTATION; FORMS;
D O I：
10.1016/j.procs.2019.01.019
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Since shape is one of the important low-level features of any Image Retrieval and any image classification system, we present in this paper a new set of orthogonal polynomials called shifted Legendre polynomials, this helps to build a set of orthogonal moments, which are Mvariant to translation, rotation and scale. We apply new image Retrieval and classification systems based on the proposed invariant moments and Radial Basis Functions Neural Networks. To show the effectiveness of our approaches we present some experimental results. (C) 2019 The Authors. Published by Elsevier B. V.
引用
收藏
页码：154 / 163
页数：10
相关论文
共 50 条
  • [41] Atmospheric temperature retrieval using a radial basis function neural network
    Laboratorio Associado de Computacao e Matematica Aplicada - LAC, Instituto Nacional de Pesquisas Espaciais - INPE, Sao Jose dos Campos, SP, Brazil
    不详
    不详
    Int. J. Inf. Commun. Technol., 2008, 2 (224-239):
  • [42] Enhanced Image Reconstruction in Electrical Impedance Tomography using Radial Basis Function Neural Networks
    Nomvussi, Serge Ayme Kouakouo
    Mikulka, Jan
    MEASUREMENT SCIENCE REVIEW, 2024, 24 (06): : 200 - 210
  • [43] Using principal component analysis and radial basis function neural networks for image contents classification
    Chang, Chuan-Yu
    Li, Chi-Fang
    Wang, Hung-Jen
    2007 THIRD INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATION HIDING AND MULTIMEDIA SIGNAL PROCESSING, VOL 1, PROCEEDINGS, 2007, : 7 - +
  • [44] Identification of rheumatoid arthritis using bone image features with radial basis function neural networks
    Bose, Anandh Sam Chandra
    Srinivasan, C.
    Surenderanath, S.
    INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, 2024, 34 (03)
  • [45] A New Image Rotation Approach Using Radial Basis Functions
    Cheng, Huifang
    Wan, Yi
    2015 8TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING (CISP), 2015, : 1026 - 1031
  • [46] Image registration using radial basis functions with adaptive radius
    Shusharina, Nadezhda
    Sharp, Gregory
    MEDICAL PHYSICS, 2012, 39 (11) : 6542 - 6549
  • [47] Estimating Diffusion Propagator and Its Moments Using Directional Radial Basis Functions
    Ning, Lipeng
    Westin, Carl-Fredrik
    Rathi, Yogesh
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2015, 34 (10) : 2058 - 2078
  • [48] Revised GMDH-type neural networks with radial basis functions and their application to medical image recognition of stomach
    Kondo, T
    MODELLING AND SIMULATION 2001, 2001, : 673 - 679
  • [49] Learning Invariant Representations for Equivariant Neural Networks Using Orthogonal Moments
    Singh, Jaspreet
    Singh, Chandan
    2022 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2022,
  • [50] Classification using networks of normalized radial basis functions.
    Bugmann, G
    INTERNATIONAL CONFERENCE ON ADVANCES IN PATTERN RECOGNITION, 1999, : 435 - 444
12345