DocumentCode :
3322976
Title :
A RBFN Perceptive Model for Image Thresholding
Author :
Lopes, Fabrício Martins ; Consularo, Luís Augusto
Author_Institution :
Centro Federal de Educação Tecnológica do Paraní
fYear :
2005
fDate :
09-12 Oct. 2005
Firstpage :
225
Lastpage :
232
Abstract :
The 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.
Keywords :
Digital images; Histograms; Humans; Image segmentation; Lighting; Pixel; Psychology; Radial basis function networks; Smoothing methods; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Graphics and Image Processing, 2005. SIBGRAPI 2005. 18th Brazilian Symposium on
ISSN :
1530-1834
Print_ISBN :
0-7695-2389-7
Type :
conf
DOI :
10.1109/SIBGRAPI.2005.8
Filename :
1599108
Link To Document :
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