Residual-driven Fuzzy <i>C</i>-Means Clustering for Image Segmentation

Cong Wang; Witold Pedrycz; ZhiWu Li; MengChu Zhou

doi:10.1109/JAS.2020.1003420

Volume 8 Issue 4

Apr. 2021

IEEE/CAA Journal of Automatica Sinica

JCR Impact Factor: 11.8, Top 4% (SCI Q1)

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2021 > 8(4): 876-889

Cong Wang, Witold Pedrycz, ZhiWu Li, and MengChu Zhou, "Residual-driven Fuzzy C-Means Clustering for Image Segmentation," IEEE/CAA J. Autom. Sinica, vol. 8, no. 4, pp. 876-889, Apr. 2021. doi: 10.1109/JAS.2020.1003420

Citation:

Cong Wang, Witold Pedrycz, ZhiWu Li, and MengChu Zhou, "Residual-driven Fuzzy C-Means Clustering for Image Segmentation," IEEE/CAA J. Autom. Sinica, vol. 8, no. 4, pp. 876-889, Apr. 2021. doi: 10.1109/JAS.2020.1003420

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Residual-driven Fuzzy C-Means Clustering for Image Segmentation

doi: 10.1109/JAS.2020.1003420

Cong Wang^1
,,
Witold Pedrycz^{2, 3, 4
,},
ZhiWu Li^{1, 5
,
,},
MengChu Zhou^{5, 6
,
,}

1.
School of Electro-Mechanical Engineering, Xidian University, Xi’an 710071, China
2.
Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6R 2V4, Canada
3.
School of Electro-Mechanical Engineering, Xidian University, Xi’an 710071, China
4.
Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
5.
Institute of Systems Engineering, Macau University of Science and Technology, Macau 999078, China
6.
Helen and John C. Hartmann Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ 07102 USA

Funds: This work was supported in part by the Doctoral Students’ Short Term Study Abroad Scholarship Fund of Xidian University, the National Natural Science Foundation of China (61873342, 61672400, 62076189) , the Recruitment Program of Global Experts, and the Science and Technology Development Fund, MSAR (0012/2019/A1)

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Author Bio:
Cong Wang received the B.S. degree in automation and the M.S. degree in mathematics from Hohai University, China, in 2014 and 2017, respectively. He is currently pursuing the Ph.D. degree in mechatronic engineering, Xidian University, China. He was a Visiting Ph.D. Student in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada. He was a Research Assistant at the School of Computer Science and Engineering, Nanyang Technological University, Singapore. He is currently a Visiting Ph.D. Student in the Department of Electrical and Computer Engineering, National University of Singapore, Singapore. His current research interests include wavelet analysis and its applications, granular computing, as well as image processing

Witold Pedrycz (M’88–SM’90–F’99) received the MS.c. degree in computer science and technology, the Ph.D. degree in computer engineering, and the D.Sci. degree in systems science from the Silesian University of Technology, Gliwice, Poland, in 1977, 1980, and 1984, respectively. He is a Professor and the Canada Research Chair in Computational Intelligence with the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada. He is also with the Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland. He is a foreign member of the Polish Academy of Sciences. He has authored 15 research monographs covering various aspects of computational intelligence, data mining, and software engineering. His current research interests include computational intelligence, fuzzy modeling, and granular computing, knowledge discovery and data mining, fuzzy control, pattern recognition, knowledge-based neural networks, relational computing, and software engineering. He has published numerous papers in the above areas. Dr. Pedrycz was a recipient of the IEEE Canada Computer Engineering Medal, the Cajastur Prize for Soft Computing from the European Centre for Soft Computing, the Killam Prize, and the Fuzzy Pioneer Award from the IEEE Computational Intelligence Society. He is intensively involved in editorial activities. He is an Editor-in-Chief of Information Sciences, an Editor-in-Chief of WIREs Data Mining and Knowledge Discovery (Wiley) and the International Journal of Granular Computing (Springer). He currently serves as a member of a number of editorial boards of other international journals. He is a Fellow of the Royal Society of Canada

ZhiWu Li (M’06–SM’07–F’16) received the B.S. degree in mechanical engineering, the M.S. degree in automatic control, and the Ph.D. degree in manufacturing engineering from Xidian University, Xi’an, China, in 1989, 1992, and 1995, respectively. He joined Xidian University in 1992. He is also currently with the Institute of Systems Engineering, Macau University of Science and Technology, Macau, China. He was a Visiting Professor with the University of Toronto, Toronto, ON, Canada, the Technion-Israel Institute of Technology, Haifa, Israel, the Martin-Luther University of Halle-Wittenburg, Halle, Germany, Conservatoire National des Arts et Métiers, Paris, France, and Meliksah Universitesi, Kayseri, Turkey. His current research interests include Petri net theory and application, supervisory control of discrete-event systems, system reconfiguration, game theory, and data and process mining. Dr. Li was a recipient of an Alexander von Humboldt Research Grant, Alexander von Humboldt Foundation, Germany. He is listed in Marquis Who’s Who in the World, 27th Edition, 2010. He serves as a Frequent Reviewer of 90+ international journals, including Automatica and a number of the IEEE Transactions as well as many international conferences. He is the Founding Chair of Xi’an Chapter of IEEE Systems, Man, and Cybernetics Society. He is a member of Discrete-Event Systems Technical Committee of the IEEE Systems, Man, and Cybernetics Society and IFAC Technical Committee on Discrete-Event and Hybrid Systems, from 2011 to 2014

MengChu Zhou (S’88–M’90–SM’93–F’03) received the B.S. degree in control engineering from Nanjing University of Science and Technology, Nanjing, China in 1983, M.S. degree in automatic control from Beijing Institute of Technology, Beijing, China in 1986, and Ph.D. degree in computer and systems engineering from Rensselaer Polytechnic Institute, Troy, NY, USA in 1990. He joined New Jersey Institute of Technology (NJIT), Newark, NJ, in 1990, and is now a Distinguished Professor of Electrical and Computer Engineering. His research interests are in Petri nets, intelligent automation, Internet of Things, big data, web services, and intelligent transportation. He has over 900 publications including 12 books, 600+ journal papers (450+ in IEEE Transactions, 26 patents and 29 book-chapters. He is the founding Editor of IEEE Press Book Series on Systems Science and Engineering, Editor-in-Chief of IEEE/CAA Journal of Automatica Sinica, and Associate Editor of IEEE Internet of Things Journal, IEEE Transactions on Intelligent Transportation Systems, and IEEE Transactions on Systems, Man, and Cybernetics: Systems. He is a recipient of Humboldt Research Award for US Senior Scientists from Alexander von Humboldt Foundation, Franklin V. Taylor Memorial Award and the Norbert Wiener Award from IEEE Systems, Man and Cybernetics Society, Excellence in Research Prize and Medal from NJIT and Edison Patent Award from the Research & Development Council of New Jersey. He is a life member of Chinese Association for Science and Technology-USA and served as its President in 1999. He is a Fellow of International Federation of Automatic Control (IFAC), American Association for the Advancement of Science (AAAS) and Chinese Association of Automation (CAA)
Corresponding author: ZhiWu Li, e-mail: zhwli@xidian.edu.cn; MengChu Zhou, e-mail: zhou@njit.edu
¹http://www.bic.mni.mcgill.ca/brainweb/
²https: //www2.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/resources.html
³http://research.microsoft.com/vision/cambridge/recognition/
⁴http://neo.sci.gsfc.nasa.gov/
⁵http://host.robots.ox.ac.uk/pascal/VOC/voc2012/index.html
Received Date: 2020-07-26
Revised Date: 2020-08-27
Accepted Date: 2020-09-24

Available Online: 2020-10-14

Abstract

Abstract

In this paper, we elaborate on residual-driven Fuzzy C-Means (FCM) for image segmentation, which is the first approach that realizes accurate residual (noise/outliers) estimation and enables noise-free image to participate in clustering. We propose a residual-driven FCM framework by integrating into FCM a residual-related regularization term derived from the distribution characteristic of different types of noise. Built on this framework, a weighted $ \ell_{2}$-norm regularization term is presented by weighting mixed noise distribution, thus resulting in a universal residual-driven FCM algorithm in presence of mixed or unknown noise. Besides, with the constraint of spatial information, the residual estimation becomes more reliable than that only considering an observed image itself. Supporting experiments on synthetic, medical, and real-world images are conducted. The results demonstrate the superior effectiveness and efficiency of the proposed algorithm over its peers.
- Fuzzy C-Means,
- image segmentation,
- mixed or unknown noise,
- residual-driven,
- weighted regularization

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¹http://www.bic.mni.mcgill.ca/brainweb/
²https: //www2.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/resources.html
³http://research.microsoft.com/vision/cambridge/recognition/
⁴http://neo.sci.gsfc.nasa.gov/
⁵http://host.robots.ox.ac.uk/pascal/VOC/voc2012/index.html

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For the first time, we propose an RFCM framework for image segmentation.
WRFCM is presented by weighting mixed noise distribution and incorporating spatial information.
We design a two-step iterative algorithm to realize WRFCM.
WRFCM is validated to produce state-of-the-art performance.

Residual-driven Fuzzy C-Means Clustering for Image Segmentation

doi: 10.1109/JAS.2020.1003420

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