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3D Shape Classification Using 3D Discrete Moments and Deep Neural Networks

Published: 27 March 2019 Publication History

Abstract

In this paper, we propose a new model for 3D shape classification based on 3D discrete orthogonal moments and deep neural network (DNN) to enhance the classification accuracy of 3D objects under geometric transformations such as scale and rotation. The proposed model is derived by introducing image moments as an input vector in DNN, frequently utilized in many tasks of pattern recognition. Discrete orthogonal moments have the ability to capture global information from an image in lower orders. The aim of this work is to investigate the robustness of the proposed model to geometric transformations like rotation and scale. The simulations are performed on constructed dataset by applying some geometric transformations on selected objects from the McGill database to evaluate the performance of our proposed model. The obtained results show that the proposed model with Hahn moments achieves high classification rates and robust to geometric transformations than Krawtchouk moments.

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Cited By

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  • (2023)Quaternion discrete orthogonal Hahn moments convolutional neural network for color image classification and face recognitionMultimedia Tools and Applications10.1007/s11042-023-14866-482:21(32827-32853)Online publication date: 2-Mar-2023
  • (2023)Fast and Accurate Color Image Classification Based on Quaternion Tchebichef Moments and Quaternion Convolutional Neural NetworkProceedings of the 3rd International Conference on Electronic Engineering and Renewable Energy Systems10.1007/978-981-19-6223-3_36(329-337)Online publication date: 1-Apr-2023
  • (2022)Quaternion Discrete Racah Moments Convolutional Neural Network for Color Face Recognition2022 International Conference on Intelligent Systems and Computer Vision (ISCV)10.1109/ISCV54655.2022.9806123(1-5)Online publication date: 18-May-2022
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cover image ACM Other conferences
NISS '19: Proceedings of the 2nd International Conference on Networking, Information Systems & Security
March 2019
512 pages
ISBN:9781450366458
DOI:10.1145/3320326
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 27 March 2019

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Author Tags

  1. 3D discrete orthogonal moments
  2. 3D shape classification
  3. deep neural network
  4. geometric transformations

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Cited By

View all
  • (2023)Quaternion discrete orthogonal Hahn moments convolutional neural network for color image classification and face recognitionMultimedia Tools and Applications10.1007/s11042-023-14866-482:21(32827-32853)Online publication date: 2-Mar-2023
  • (2023)Fast and Accurate Color Image Classification Based on Quaternion Tchebichef Moments and Quaternion Convolutional Neural NetworkProceedings of the 3rd International Conference on Electronic Engineering and Renewable Energy Systems10.1007/978-981-19-6223-3_36(329-337)Online publication date: 1-Apr-2023
  • (2022)Quaternion Discrete Racah Moments Convolutional Neural Network for Color Face Recognition2022 International Conference on Intelligent Systems and Computer Vision (ISCV)10.1109/ISCV54655.2022.9806123(1-5)Online publication date: 18-May-2022
  • (2022)Rigid and non-rigid 3D shape classification based on 3D Hahn moments neural networks modelMultimedia Tools and Applications10.1007/s11042-022-12125-681:26(38067-38090)Online publication date: 1-Nov-2022
  • (2022)Efficient color face recognition based on quaternion discrete orthogonal moments neural networksMultimedia Tools and Applications10.1007/s11042-021-11669-381:6(7685-7710)Online publication date: 1-Mar-2022
  • (2020)Enhancing the Performance of Grayscale Image Classification by 2D Charlier Moments Neural NetworksProceedings of the 2nd International Conference on Electronic Engineering and Renewable Energy Systems10.1007/978-981-15-6259-4_14(151-159)Online publication date: 15-Aug-2020

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