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一种加权的多重分形特征提取算法

谢雅婷 梁光明 石跃祥 柳佳雯 丁建文

计算机工程与应用2013,Vol.49Issue(4):206-208,3.
计算机工程与应用2013,Vol.49Issue(4):206-208,3.DOI:10.3778/j.issn.1002-8331.1107-0113

一种加权的多重分形特征提取算法

Weighted multi-fractal algorithm for feature extraction

谢雅婷 1梁光明 2石跃祥 1柳佳雯 1丁建文3

作者信息

  • 1. 湘潭大学信息工程学院,湖南湘潭411105
  • 2. 国防科技大学电子科学与工程学院,长沙410075
  • 3. 长沙爱威科技,长沙410013
  • 折叠

摘要

Abstract

In order to solve the drawbacks of the multi-fractal dimension can not be a good reflection of the image intensity information and highly dependes on the image scale, this paper presents two improvement based on q-order moments of general dimension theory, marked D(q). This paper proposes a new weighted calculation of boxes number method conbined intensity information by analyzing the factors affecting the probability of growth, then proposes a two-dimensional method of calculating fractal dimension based on the gride intensity and mean. Experiment shows that the new method improves features differenta-tion, computes features more robust and more effective, and improves the classification accuracy by putting the new method in the identification systerm of blood cells.

关键词

特征提取/多重分形/网格/生长概率

Key words

feature extraction/malti-fractal/gride/growth proability

分类

信息技术与安全科学

引用本文复制引用

谢雅婷,梁光明,石跃祥,柳佳雯,丁建文..一种加权的多重分形特征提取算法[J].计算机工程与应用,2013,49(4):206-208,3.

基金项目

湖南省自然科学基金(No.07JJ6115) (No.07JJ6115)

智能制造湖南省高校重点实验室(No.2009IM06). (No.2009IM06)

计算机工程与应用

OACSCDCSTPCD

1002-8331

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