Earticle

초록

영어

The traditional image retrieval method is based on single feature retrieval method like color, texture, shape or multi feature weighted fusion method. The retrieval rate of existing methods is not high. This paper presents fusion multi feature image retrieval. Two kinds of feature play a complementary effect in retrieval. Most color feature can not reflect the spatial information of image. Texture is a regional characteristics which contains important spatial information of image. Fusing the color and texture feature can play their respective advantages. At the same time, avoiding the one-sidedness of single feature retrieval. Improving the retrieval accuracy and flexibility well.

목차

Abstract
 1. Introduction
 2. Dempster-Shafer Evidence Theory
  2.1. Frame of Discernment
  2.2. Basic Probability Assignment-BPA
  2.3. Belief Function
  2.4. Plausibility Function
 3. The Experiment of Image Retrieval based on Multi Feature DS Evidence Theory Fusion
  3.1. Dempster Rule of Evidential Combination
  3.2. Experimental Procedure
 4. Testing Results and Analysis
  4.1. Image Retrieval Algorithm based on More Color Feature Combination
  4.2. Image Retrieval Algorithm based on Gabor Texture Feature Combination
  4.3. Image Retrieval Algorithm based on Integrated Multi Feature Combination
 5. Conclusion
 References

키워드

저자

• Che Chang [ Measuring and Control Technology and Instrumentations Harbin University of Science and Technology, School of Engineering, Harbin University, Harbin, China ] Corresponding author
• Yu Xiaoyang [ Measuring and Control Technology and Instrumentations Harbin University of Science and Technology ]
• Yu Guang [ Measuring and Control Technology and Instrumentations Harbin University of Science and Technology ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605