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Zhang H, Cai Z, Xiao L, Heidari AA, Chen H, Zhao D, Wang S, Zhang Y. Face Image Segmentation Using Boosted Grey Wolf Optimizer. Biomimetics (Basel) 2023; 8:484. [PMID: 37887615 PMCID: PMC10604473 DOI: 10.3390/biomimetics8060484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 10/03/2023] [Accepted: 10/06/2023] [Indexed: 10/28/2023] Open
Abstract
Image segmentation methods have received widespread attention in face image recognition, which can divide each pixel in the image into different regions and effectively distinguish the face region from the background for further recognition. Threshold segmentation, a common image segmentation method, suffers from the problem that the computational complexity shows exponential growth with the increase in the segmentation threshold level. Therefore, in order to improve the segmentation quality and obtain the segmentation thresholds more efficiently, a multi-threshold image segmentation framework based on a meta-heuristic optimization technique combined with Kapur's entropy is proposed in this study. A meta-heuristic optimization method based on an improved grey wolf optimizer variant is proposed to optimize the 2D Kapur's entropy of the greyscale and nonlocal mean 2D histograms generated by image computation. In order to verify the advancement of the method, experiments compared with the state-of-the-art method on IEEE CEC2020 and face image segmentation public dataset were conducted in this paper. The proposed method has achieved better results than other methods in various tests at 18 thresholds with an average feature similarity of 0.8792, an average structural similarity of 0.8532, and an average peak signal-to-noise ratio of 24.9 dB. It can be used as an effective tool for face segmentation.
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Affiliation(s)
- Hongliang Zhang
- Jilin Agricultural University Library, Jilin Agricultural University, Changchun 130118, China;
| | - Zhennao Cai
- College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, China; (Z.C.); (L.X.)
| | - Lei Xiao
- College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, China; (Z.C.); (L.X.)
| | - Ali Asghar Heidari
- School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran 11366, Iran;
| | - Huiling Chen
- College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, China; (Z.C.); (L.X.)
| | - Dong Zhao
- College of Computer Science and Technology, Changchun Normal University, Changchun 130032, China
| | - Shuihua Wang
- School of Computing and Mathematical Sciences, University of Leicester, Leicester LE1 7RH, UK;
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China
- School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454000, China
| | - Yudong Zhang
- School of Computing and Mathematical Sciences, University of Leicester, Leicester LE1 7RH, UK;
- School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454000, China
- Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia
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Szczuko P, Harasimiuk A, Czyżewski A. Evaluation of Decision Fusion Methods for Multimodal Biometrics in the Banking Application. SENSORS 2022; 22:s22062356. [PMID: 35336526 PMCID: PMC8951111 DOI: 10.3390/s22062356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 03/14/2022] [Accepted: 03/16/2022] [Indexed: 11/16/2022]
Abstract
An evaluation of decision fusion methods based on Dempster-Shafer Theory (DST) and its modifications is presented in the article, studied over real biometric data from the engineered multimodal banking client verification system. First, the approaches for multimodal biometric data fusion for verification are explained. Then the proposed implementation of comparison scores fusion is presented, including details on the application of DST, required modifications, base probability, and mass conversions. Next, the biometric verification process is described, and the engineered biometric banking system principles are provided. Finally, the validation results of three fusion approaches on synthetic and real data are presented and discussed, considering the desired outcome manifested by minimized false non-match rates for various assumed thresholds and biometric verification techniques.
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Czyżewski A, Hoffmann P, Szczuko P, Kurowski A, Lech M, Szczodrak M. Analysis of results of large‐scale multimodal biometric identity verification experiment. IET BIOMETRICS 2018. [DOI: 10.1049/iet-bmt.2018.5030] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Affiliation(s)
- Andrzej Czyżewski
- Multimedia Systems DepartmentGdańsk University of Technology, Faculty of Electronics, Telecommunication and Informaticsul. Narutowicza 11/12GdańskPoland
| | - Piotr Hoffmann
- Multimedia Systems DepartmentGdańsk University of Technology, Faculty of Electronics, Telecommunication and Informaticsul. Narutowicza 11/12GdańskPoland
| | - Piotr Szczuko
- Multimedia Systems DepartmentGdańsk University of Technology, Faculty of Electronics, Telecommunication and Informaticsul. Narutowicza 11/12GdańskPoland
| | - Adam Kurowski
- Multimedia Systems DepartmentGdańsk University of Technology, Faculty of Electronics, Telecommunication and Informaticsul. Narutowicza 11/12GdańskPoland
| | - Michał Lech
- Multimedia Systems DepartmentGdańsk University of Technology, Faculty of Electronics, Telecommunication and Informaticsul. Narutowicza 11/12GdańskPoland
| | - Maciej Szczodrak
- Multimedia Systems DepartmentGdańsk University of Technology, Faculty of Electronics, Telecommunication and Informaticsul. Narutowicza 11/12GdańskPoland
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