Reference TypeConference Proceedings
Citation KeyLopesCons:2005:RBPeMo
Author1 Lopes, Fabrício Martins
2 Consularo, Luís Augusto
Affiliation1 CEFET-PR - Centro Federal de Educação Tecnológica do Paraná
2 Av. Alberto Carazzai, 1640, 86300-000, Cornélio Procópio, PR, Brasil.
3 UNIMEP - Universidade Metodista de Piracicaba
4 Rodovia do Açúcar, Km 156, 13400-911, Piracicaba, SP, Brasil.
TitleA RBFN perceptive model for image thresholding
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 18 (SIBGRAPI)
EditorRodrigues, Maria Andréia Formico
Frery, Alejandro César
Book TitleProceedings
Date9-12 Oct. 2005
Publisher CityLos Alamitos
PublisherIEEE Computer Society
Conference LocationNatal
KeywordsSegmentation, Thresholding, RBFN, Psychophysical.
AbstractThe digital image segmentation challenge has demanded the development of a plethora of methods and approaches. A quite simple approach, the thresholding, has still been intensively applied mainly for real-time vision applications. However, the threshold criteria often depend on entropic or statistical image features. This work searches a relationship between these features and subjective human threshold decisions. Then, an image thresholding model based on these subjective decisions and global statistical features was developed by training a Radial Basis Functions Network (RBFN). This work also compares the automatic thresholding methods to the human responses. Furthermore, the RBFN-modeled answers were compared to the automatic thresholding. The results show that entropic-based method was closer to RBFN-modeled thresholding than variance-based method. It was also found that another automatic method which combines global and local criteria presented higher correlation with human responses.
Tertiary TypeFull Paper
Size385 KiB
Number of Files1
Target Filelopesf_rbfnperceptive.pdf
Last Update2005: administrator
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History2005-07-15 21:19:21 :: -> banon ::
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Access Date2020, Nov. 27