JOURNAL BROWSE
Search
Advanced SearchSearch Tips
An α-cut Automatic Set based on Fuzzy Binarization Using Fuzzy Logic
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
An α-cut Automatic Set based on Fuzzy Binarization Using Fuzzy Logic
Lee, Ho Chang; Kim, Kwang Baek; Park, Hyun Jun; Cha, Eui-Young;
  PDF(new window)
 Abstract
Image binarization is a process to divide the image into objects and backgrounds, widely applied to the fields of image analysis and its recognition. In the existing method of binarization, there is some uncertainty when there is insufficient brightness gap between objects and backgrounds in setting threshold. The method of fuzzy binarization has improved the features of objects efficiently. However, since this method sets -cut value statically, there remain some problems that important features of objects can be lost during binarization. Therefore, in this paper, we propose a binarization method which does not set -cut value statically. The proposed method uses fuzzy membership functions calculated by thresholds of mean, iterative, and Otsu binarization. Experiment results show the proposed method binaries various images with less loss than the existing methods.
 Keywords
Image Processing;Fuzzy Binarization;Fuzzy Logic;Fuzzy Arithmetic Operation;Image Enhancement;
 Language
Korean
 Cited by
 References
1.
A. Rosenfeld and A.C. Kak, Digital Picture Processing, 2nd ed. Academic Press, 1982.

2.
M. Sonka, V. Hlavac, and R. Boyle, Image Processing Analysis, and Machine Vision, 2nd ed. PWS Publishing, 2014.

3.
N. Otsu, "A threshold selection method from grey-level histogram," IEEE Trans. SMC, vol. 9, no. 1, pp. 62-66, 1979.

4.
J. N. Kapur, P. K. Sahoo, and A. Wong, "A New Method for Gray Lavel Picture using Entropy of the Histogram," Computer Vision, Graphics, and Image Processing, vol. 29, no. 3, pp. 273-285, 1985. crossref(new window)

5.
J. Bernsen, "Dynamic thresholding of grey-level images," In International conference on pattern recognition, pp. 1251-1255, 1986.

6.
D. S. Hong, Introduction to Fuzzy Systems For Engineers, Moonwoondang, pp. 108-110, 2010.

7.
D. Coker, "An introduction to intuitionistic fuzzy topological spaces," Fuzzy sets and systems, vol. 88, no. 1, pp. 81-89, 1997. crossref(new window)

8.
K. B. Kim, "ART2 Based Fuzzy Binarization Method with Low Information Loss," Journal of the Korea Institute of Information and Communication Engineering, vol. 18, no. 6, pp. 1269-1274, Jun. 2014. crossref(new window)

9.
B. J Chae, K. B. Kim, "Max-Min Neural Networks using Fuzzy Control Method," Journal of the Korea Institute of Electronic Communication Sciences, vol. 7, no. 1, pp. 95-98 Jun. 2013.

10.
K. B. Kim, "Fuzzy Stretching Method of Color Image," Journal of the Korea Society of Computer and Information, vol. 18, no. 5, May. 2013.