caa a22 4500 605470707 CHVBK 20210128100329.0 cr unu---uuuuu 210128e20150201xx s 000 0 eng 10.1007/s00500-014-1256-2 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1256-2 An iterative fuzzy region competition algorithm for multiphase image segmentation [Elektronische Daten] [V. Borges, D. Guliato, C. Barcelos, M. Batista] This paper presents a new multiphase image segmentation model based on Fuzzy Region Competition. The proposed model approximates image regions by probability density functions and uses a supervised approach in the segmentation process. The strategy of the proposed model is to perform a two-phase Fuzzy Region Competition model iteratively for image segmentation. The hard partition is obtained in each step from a determined fuzzy membership functions consequently, the segmentation process is soft, while the final result is hard, due to the simplicity of avoiding non-overlapping and vacuum regions. Finally, several experiments on multiphase images are presented to demonstrate the efficiency and robustness of the proposed model when dealing with noisy, texturized and natural images. Springer-Verlag Berlin Heidelberg, 2014 Variational methods nationallicence Multiphase segmentation nationallicence Probability density functions nationallicence Fuzzy region competition nationallicence Borges V. School of Computing, Federal University of Uberlândia, Uberlândia, Minas Gerais, Brazil aut Guliato D. School of Computing, Federal University of Uberlândia, Uberlândia, Minas Gerais, Brazil aut Barcelos C. School of Computing, Federal University of Uberlândia, Uberlândia, Minas Gerais, Brazil aut Batista M. Computer Science Department, Campus Catalão, Federal University of Goiás, Catalão, Goiás, Brazil aut Soft Computing Springer Berlin Heidelberg 19/2(2015-02-01), 339-351 1432-7643 19:2<339 2015 19 500 https://doi.org/10.1007/s00500-014-1256-2 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1256-2 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Borges V. School of Computing, Federal University of Uberlândia, Uberlândia, Minas Gerais, Brazil aut NATIONALLICENCE 700 1- Guliato D. School of Computing, Federal University of Uberlândia, Uberlândia, Minas Gerais, Brazil aut NATIONALLICENCE 700 1- Barcelos C. School of Computing, Federal University of Uberlândia, Uberlândia, Minas Gerais, Brazil aut NATIONALLICENCE 700 1- Batista M. Computer Science Department, Campus Catalão, Federal University of Goiás, Catalão, Goiás, Brazil aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/2(2015-02-01), 339-351 1432-7643 19:2<339 2015 19 500