Earticle

초록

영어

Art image databases play an important role in the image research history. Art image can be classified into various categories, and each category has its own characteristics. Art image retrieval with high precision and speed can help the researchers understand an art image much more easily. In addition, the classification for the art images can help the researchers improve the working efficiency. In the art image retrieval, the query precision is much more important than the query speed. Improving the query precision at the cost of not seriously decreasing the query speed can be accepted. In this paper, a new method has been proposed to improve the query precision. The new method mainly includes initial query, reorganization, results recheck and images reordering. At the beginning, the tag query method and the semantic query method will be used to search the initial image results; then, the results will be reorganization according to the semantic method; finally, the images in the results will be filtered by the incomplete filtration method. According to the experimental results, the new method is proved that it can improve the query precision. The new method can be used in the art image retrieval process.

목차

Abstract
 1. Introduction
 2. The Basic Query Methods
 3. A New Art Image Query Method
  3.1. Hierarchical Semantic Retrieval
  3.2. Image Incomplete Filtration
  3.3. The New Method
 4. Verification
 5. Conclusion
 References

키워드

저자

• Cheng Mao [ No. 289 Lingyusi Street. Baoding, Hebei Province, P.R.C ]
• Chai Wenlei [ No.180 Wusidong Road. Baoding, Hebei Province, P.R.C ]
• Wang Fuqiang [ No.402 Peace west road, Shijiazhuang, Hebei Province, P.R.C ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605