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
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)