@Article{KarmakarDool:2002:GeFuRu,
               author = "Karmakar, Gour C. and Dooley, Laurence S.",
                title = "A generic fuzzy rule based image segmentation algorithm",
              journal = "Pattern Recognition Letters",
                 year = "2002",
               volume = "23",
               number = "10",
                pages = "1215--1227",
                month = "August",
                 note = "{}",
             keywords = "generic fuzzy rules, image segmentation, spatial information, 
                         fuzzy clustering.",
             abstract = "Fuzzy rule based image segmentation techniques tend in general, to 
                         be application dependent with structure of the merbership 
                         functions being predefined and in certain cases, the corresponding 
                         parameters being manually determined. The net result is that the 
                         overall performance of the segmentation technique is very 
                         sensitive to parameter value selections. This paper addresses 
                         these issues by introducing a generic fuzzy rule based image image 
                         segmentation (GFRIS) algorithm, which is both application 
                         independent and exploits inter-pixel spatial relationships. The 
                         GFRIS algorithm automatically approximates both the key weighting 
                         factor and threshold value in the definitions of the fuzzy rule 
                         and neighbourhood system, respectively. A quantitative evaluation 
                         is presented between the segmentation results obtained using GFRIS 
                         and the popular fuzzy c-means (FCM) and possibilistic c-means 
                         (PCM) algorithms. The results demonstrate that GFRIS exhibits a 
                         considerable improvement in performance compared to both FCM abd 
                         PCM, for many different image types.",
           copyholder = "faria - tese",
        urlaccessdate = "03 maio 2024"
}