Earticle

초록

영어

A novel approach of Content Based Image Retrieval(CBIR), which combines color, texture and shape descriptors to represent the features of the image, is discussed in this paper. The proposed scheme is based on three noticeable algorithms: color distribution entropy(CDE), color level co-occurrence(CLCM) and invariant moments. CDE takes the correlation of the color spatial distribution in an image into consideration. CLCM matrix is the texture feature of the image, which is a new proposed descriptor that is grounded on co-occurrence matrix to seize the alteration of the texture. Hu invariant moments are frequently used owing to its invariance under translation, changes in scale, and also rotation. The proposed scheme achieves a modest retrieval result by utilizing these diverse and primitive image descriptors, at the same time, the retrieval result is better when use the texture feature alone which we proposed than use gray level co-occurrence. The similarity measure matrix is based upon Euclidean distance.

목차

Abstract
 1. Introduction
 2. Color Feature Represention
  2.1. Annular Color Histogram
  2.2. Color Distribution Entropy (CDE)
 3. Texture Presentation
  3.1. Color Level Co-Occurrence Matrix(CLCM)
 4. The Hu Moments based Shape Descriptor
 5. Similarity Measure
  5.1. Color Feature Similarity Measure
  5.2. Texture Feature Similarity Measure
  5.3. Shape Feature Similarity Measure
 6. Experiment Results
 7. Conclusion
 References

키워드

저자

• Zhijie Zhao [ School of Computer and Information Engineering, Harbin University of commerce ]
• Qin Tian [ School of Computer and Information Engineering, Harbin University of commerce ]
• Huadong Sun [ School of Computer and Information Engineering, Harbin University of commerce ]
• Xuesong Jin [ School of Computer and Information Engineering, Harbin University of commerce ]
• Junxi Guo [ School of Software, Harbin Institute of Technology Harbin, 150028, China ]

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