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ABSTRACT
An oil spill is a major problem for marine life. This spilled oil affects marine life and disturbs the ecosystem. To overcome this problem, SAR sensors have been utilized in marine units to find oil spills because they are free from cloudiness and sun radiation. Even though the oil spill can be detected in SAR images, the processing time and approach are complex. Several techniques have been proposed for the detection of oil spills using matching algorithms, morphological processes, and clustering. But those techniques require multiple processing steps and algorithms for detection. It also depends on user values for detection. Hence, in this paper, the detection of the oil spill in SAR images is automated by utilizing an optimized deep-learning approach. The deep learning approach automatically detects the spilled region using a trained network. Here, the hybrid Moth flame and particle swarm algorithms are used for finding the hyperparameters for training the deep learning network. With this optimized deep learning approach, the oil spill can be detected automatically and its performance verified by implementing the proposed approach in the MATLAB R2020b version. The proposed method’s performance is evaluated and compared with the existing technique using accuracy, sensitivity, specificity, Jaccard, and dice. The proposed method produces 99.64% accuracy, which is very high, and only 0.2 classification error, which is very less compared to the existing methods.
Acknowledgements
There is no acknowledgment involved in this work.
Disclosure statement
No potential conflict of interest was reported by the authors.
Ethics Approval and Consent to Participate
No participation of humans takes place in this implementation process
Human and Animal Rights
No violation of Human and Animal Rights is involved.
Additional information
Funding
Notes on contributors
Senthil Murugan J
Dr. J. Senthil Murugan., M.C.A., M.Tech (C.S.E)., Ph.D (C.S.E)., Associate Professor, Department of Computer Science and Engineering, working in VEL TECH HIGH TECH Dr.Rangarajan Dr.Sakunthala Engineering College, No:60, Avadi-Vel Tech Road, Avadi, chennai-600 062, Tamil Nadu India. He has pursued his Ph.D (CSE) from St.Peter's Institute of Higher Education and Research, Avadi, Chennai-54, and M.Tech (CSE) from SRM UNIVERSITY, Ramapuram, Chennai-89, and M.C.A from PIMSCA, M.G.R Groups, Madhuravoyal, Chennai-600095. He has Published 3 SCI Indexed Journals, 17 Scopus Indexed Journals, 2 UGC Journal, 23 National Journals, 13 Patents, and 5 Book Chapter, and 3 Text Books Published, and also having Membership with CSI Society and Others. He has Guided many PG & UG students and Coordinated with many academic related activities. He has attended many FDP, Certificate Course, R&D works, Conference, Workshop, Seminars and also conducted. His research work mainly focused on Image Processing, Networking, IoT & Image Enhancement.
Parthasarathy V
Prof. Dr. V. Parthasarathy graduated with a Bachelor of Engineering in Electrical and Electronics Engineering from the Government College of Technology, Coimbatore. Further, he has completed his post-graduation for Master of Engineering in Computer Science and Engineering from College of Engineering, Guindy, Anna University, and Ph.D. in Information and Communication engineering from Anna University, Tamil Nādu, India. He presently works as a Professor & Dean (R&D and Industry Relations) at Karpagam Academy of Higher Education (Deemed to be University), Tamil Nādu, India. His research interests include the Internet of Things, Wireless Sensor Networks, Biomedical Informatics, Next-Generation Communication Networks, and Artificial Intelligence. He has published over 100 scientific papers in reputed journals and conferences, two patents to his credit, and co-authored two book chapters. He is an Associate Editor/editorial board member and guest editor of international journals. Besides, he is a reviewer in several peer-reviewed journals. He serves/ served in many conferences as Chair / Co-Chair and delivered keynotes. He is a senior member of IEEE and a member of many professional societies such as ISTE, ACM, OSA, etc.; He is the recipient of the Indian Government’s Fund for Improvement of Science and Technology (FIST) project, Funded project from Department of Science and Technology (DST), Mentor for the DBT NER Project and Co-investigator for the project grant from Defense Research and Development Organization (DRDO).