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Transition region-based single-object image segmentation
Affiliation:1. Department of Computer Science, Minjiang University, Fuzhou 350108, China;2. School of Information Engineering, Jingdezhen Ceramic Institute, Jingdezhen 333403, China;3. School of Communication Engineering, Nanjing Institute of Technology, Nanjing 211167, China;4. School of Information Technology, Jinling Institute of Technology, Nanjing 211169, China;1. Department of Electronics and Telecommunications Engineering, Universidad Politécnica de Puebla, Tercer Carril del Ejido “Serrano” S/N, San Mateo Cuanalá, Juan C. Bonilla, Puebla, Mexico;2. ICD Group, University of Twente, Building Carré (Building No. 15), P.O. Box 217, 7500 AE Enschede, The Netherlands;3. Instituto Nacional de Astrofísica, Óptica y Electrónica, Luis Enrique Erro No. 1, Santa María Tonantzintla, Puebla, Mexico;1. Master student in Industrial Education (Electrical Communication Engineering), Faculty of Industrial Education, King Mongkut''s Institute of Technology Ladkrabang, Bangkok 10520, Thailand;2. Department of Electrical Engineering, Faculty of Military Technology, University of Defence Brno, Kounicova 65, 662 10 Brno, Czech Republic;3. Institute of Microelectronics, Faculty of Electrical Engineering and Communications, Brno University of Technology, Technická 10, 616 00 Brno, Czech Republic;4. Department of Engineering Education, Faculty of Industrial Education, King Mongkut''s Institute of Technology Ladkrabang, Bangkok 10520, Thailand
Abstract:
Keywords:Local variance  Transition region  Image thresholding  Image segmentation
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