Earticle

초록

영어

Color information recognition methods based on the RGB color model, which is designed on the basis of static fuzzy inference rules, are being widely used at present. However, these methods have certain limitations because of the nature of the model used: detachment of human vision and limited choice of environment. In this paper, we propose a method based on the HSI model and a new inference process that resembles the human vision recognition process. This method allows the user to add, delete, or update inference rules. In our method, membership intervals are designed with sine and cosine functions in the H channel and trigonometric style functions in the S and I channels. The membership degree is computed via an interval merging process. Then, inference rules are applied to the result in order to infer the color information. Experimental results show that our method is more intuitive and ecient than that based on the RGB model.

목차

Abstract
 1. Introduction
 2. Proposed method of color information analysis
  2.1. Color inference using the HSI model
  2.2. Eleven basic inference rules
  2.3. Membership interval merger
  2.4. Changing inference rules
  2.5. Processing for redundant inference rules
 3. Experimental analysis and results
  3.1. Comparison with conventional color recognition model
  3.2. Results of membership interval merger
  3.3. Results of add, modify, delete inference rules
 4. Conclusion
 Acknowledements
 References

키워드

저자

• Sang-Geol Lee [ Dept. of Computer Engineering, Pusan National University ]
• Kwang-Baek Kim [ Dept. of Computer Engineering, Silla University ]
• Eui-Young Cha [ Dept. of Computer Engineering, Pusan National University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605