Optimization of interval type-2 fuzzy systems for image edge detection |
| |
| Affiliation: | 1. Autonomous University of Baja California, Tijuana, Mexico;2. Tijuana Institute of Technology, Tijuana, Mexico;1. Chair on System Science and the Energetic Challenge, Fondation Électricité de France (EDF), CentraleSupélec, Université Paris-Saclay, Grande Voie des Vignes, 92290 Châtenay-Malabry, France;2. Energy Departement, Politecnico di Milano, Campus Bovisa, Via Lambruschini 4, 20156 Milano, Italy;1. School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing 210044, China;2. Centre for Computational Intelligence (CCI), School of Computer Science and Informatics, De Montfort University, Leicester LE1 9BH, United Kingdom;1. REsearch Groups in Intelligent Machines (REGIM-Lab), University of Sfax, National School of Engineers (ENIS), BP 1173, Sfax 3038, Tunisia;2. Faculty of Electrical Engineering and Computer Science, Technical University of Ostrava, Czech Republic;3. Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, WA, USA,;1. Department of Computer Science & Engineering, Cooch Behar Government Engineering College, Cooch Behar, West Bengal, India;2. Department of Information Technology, RCC Institute of Information Technology, Kolkata, West Bengal 700015, India;3. Department of Computer and System Sciences, Visva-Bharati University, Santiniketan 721 325, India |
| |
| Abstract: | This paper presents the optimization of a fuzzy edge detector based on the traditional Sobel technique combined with interval type-2 fuzzy logic. The goal of using interval type-2 fuzzy logic in edge detection methods is to provide them with the ability to handle uncertainty in processing real world images. However, the optimal design of fuzzy systems is a difficult task and for this reason the use of meta-heuristic optimization techniques is also considered in this paper. For the optimization of the fuzzy inference systems, the Cuckoo Search (CS) and Genetic Algorithms (GAs) are applied. Simulation results show that using an optimal interval type-2 fuzzy system in conjunction with the Sobel technique provides a powerful edge detection method that outperforms its type-1 counterparts and the pure original Sobel technique. |
| |
| Keywords: | Interval type-2 fuzzy logic Edge detection Image processing Cuckoo Search algorithms |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
