Journal of Frontiers of Computer Science and Technology ›› 2009, Vol. 3 ›› Issue (4): 423-432.DOI: 10.3778/j.issn.1673-9418.2009.04.009

• 学术研究 • Previous Articles     Next Articles

A Fast Image Retrieval Method Based on Fractal Codes

WANG Xingyuan, CHEN Zhifeng   

  1. Institute of Computer Application, School of Electronic & Information Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-07-15 Published:2009-07-15
  • Contact: WANG Xingyuan



  1. 大连理工大学 电子与信息工程学院 计算机应用研究所,辽宁 大连 116024
  • 通讯作者: 王兴元

Abstract: For the content-based image retrieval (CBIR) in fractal domain, a fast fractal encoding method is proposed to extract image features, which is based on a novel no-search and adaptive quadtree division. As a result, the fractal coding speed is significantly improved, it only needs 0.048 5 s on average for a 256×256 image and is approximately 70 times faster than He’s algorithm besides better reconstructed image quality. Furthermore, image matching Hong’s algorithm is also improved, enhanced the query accuracy consequently. In addition, a method to further accelerate image retrieval is presented based on the analysis to the distance and number of the fractal codes.

Key words: fractal coding, non-searching, average block, content-based image retrieval

摘要: 针对分形域上的基于内容的图像检索(content-based image retrieval,CBIR),提出了一种新颖的基于无搜索的自适应四叉树分割的快速分形编码方法,来提取图像特征,从而使图像检索的编码阶段速度显著提高。对一幅256×256图像编码,算法平均约需0.048 5 s,比何的方法约快70倍,并且解码图像质量良好。改进了匹配算法来实现图像的快速检索,其准确性要高于洪的方法;最后通过对分形码距及分形码块数的分析,提出了进一步提高检索速度的方案。

关键词: 分形编码, 无搜索, 平均块, 基于内容的图像检索