Ultrafuzziness Optimization Based on Type II Fuzzy Sets for Image Thresholding

Agus Zainal Arifin (Laboratory of Vision and Image Processing, Department of Informatics Faculty of Information Technology, Institut Teknologi Sepuluh Nopember (ITS))
Aidila Fitri Fitri Heddyanna (Laboratory of Vision and Image Processing, Department of Informatics Faculty of Information Technology, Institut Teknologi Sepuluh Nopember (ITS))
Hudan Studiawan (Laboratory of Vision and Image Processing, Department of Informatics Faculty of Information Technology, Institut Teknologi Sepuluh Nopember (ITS))

Journal of ICT Research and Applications
Vol. 4 No. 2 (2010)

Image thresholding is one of the processing techniques to provide high quality preprocessed image. Image vagueness and bad illumination are common obstacles yielding in a poor image thresholding output. By assuming image as fuzzy sets, several different fuzzy thresholding techniques have been proposed to remove these obstacles during threshold selection. In this paper, we proposed an algorithm for thresholding image using ultrafuzziness optimization to decrease uncertainty in fuzzy system by common fuzzy sets like type II fuzzy sets. Optimization was conducted by involving ultrafuzziness measurement for background and object fuzzy sets separately. Experimental results demonstrated that the proposed image thresholding method had good performances for images with high vagueness, low level contrast, and grayscale ambiguity.