Earticle

초록

영어

With the development of society, number of art image becomes bigger and bigger. In order to classify the art images, it is necessary to retrieve the images with common features. Different from the commonly used image query method, art images are always seen by specific researchers and to study and classification, and it is much more important for the query method with high retrieval precision. So it is important to develop a better query method specifically used for the art image query. The main work of this paper is to establish a combined method to improve the art image query precision without decreasing the query time seriously. The combined query method includes several steps: (1) Initial query. The tag query method and the semantic query method will be used. The initial query results includes the results searched by both the methods. (2) Reorganization of the initial query results. The repeated images will be cleared and only one image will be left. (3) Distance based results rechecked. The most relative image will be ranked in front of the list and the less correlation image will be cleared. (4) Reordering the images. All the images will be reordered by the distance which reflects the correlation of the query image. According to the experimental verification, the combined method can improve the query precision.

목차

Abstract
 1. Introduction
 2. Typical Reordering Methods
 3. The Combined Search Method
  3.1. Semantic Retrieval
  3.2 Distance Matching Method
  3.3. The Combined Query 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