Earticle

초록

영어

Image binarization is divided into global algorithm and local algorithm. Global binarization algorithms have a problem to describe objects that have similar brightness with a single threshold. Local binarization algorithms make boundary lines because these algorithms split the image into a specific size of blocks. Therefore, in this paper, we propose a binarization method to complement these problems. The proposed method uses triangular fuzzy membership function to classify the image into obvious regions and ambiguous regions. Obvious regions are binarized by using global binarization algorithm. Whereas ambiguous regions are binarized by using improved local algorithm. Experimental results show the proposed method binarizes the image with less information loss. Moreover, binarized image describes the object in more detail than global binarization methods and more natural than local binarization method.

목차

Abstract
 1. Introduction
 2. Improved Binarization by Using Fuzzy Logic
  2.1. Fuzzy Logic Based Region Classification
  2.2. Binarization of Classified Regions
 3. Experiment and Analysis
 4. Conclusions
 References

키워드

저자

• Ho Chang Lee [ Dept. of Information System Engineering, Pusan National University, Busan, Korea ]
• Kwang Baek Kim [ Dept. of Computer Engineering, Silla University, Busan, Korea ]
• Hyun Jun Park [ Dept. of Computer Engineering, Pusan National University, Busan, Korea ]
• Eui-Young Cha [ Dept. of Computer Engineering, Pusan National University, Busan, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Software Engineering and Its Applications

• 간기

  월간

• pISSN

  1738-9984

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605