Open Access
ARTICLE
Enhanced Robotic Vision System Based on Deep Learning and Image Fusion
1 Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, 84428, Saudi Arabia
2 Department of the Robotics and Intelligent Machines, Faculty of Artificial Intelligence, KafrelSheikh University, Kafrelsheikh, 33511, Egypt
3 Department of Information Technology, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, 84428, Saudi Arabia
4 Department of Industrial Electronics and Control Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt
5 Department Electronics and Electrical Communications, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt
6 Department of Electronics and Communications, Faculty of Engineering, Zagazig University, Zagazig, 44519, Egypt
* Corresponding Author: Abeer D. Algarni. Email:
Computers, Materials & Continua 2022, 73(1), 1845-1861. https://doi.org/10.32604/cmc.2022.023905
Received 26 September 2021; Accepted 30 March 2022; Issue published 18 May 2022
Abstract
Image fusion has become one of the interesting fields that attract researchers to integrate information from different image sources. It is involved in several applications. One of the recent applications is the robotic vision. This application necessitates image enhancement of both infrared (IR) and visible images. This paper presents a Robot Human Interaction System (RHIS) based on image fusion and deep learning. The basic objective of this system is to fuse visual and IR images for efficient feature extraction from the captured images. Then, an enhancement model is carried out on the fused image to increase its quality. Several image enhancement models such as fuzzy logic, Convolutional Neural Network (CNN) and residual network (ResNet) pre-trained model are utilized on the fusion results and they are compared with each other and with the state-of-the-art works. Simulation results prove that the fuzzy logic enhancement gives the best results from the image quality perspective. Hence, the proposed system can be considered as an efficient solution for the robotic vision problem with multi-modality images.Keywords
Cite This Article
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.