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关于二维植物的数学重建

On the mathematical reconstruction of two dimensional plants.

作者信息

Grzywna Zbigniew J, Borys Przemysław, Dudek Gabriela

机构信息

Section of Physics and Applied Mathematics, Faculty of Chemistry, Silesian University of Technology, Ks. M. Strzody 9, 44-100 , Gliwice, Poland.

出版信息

Biosci Rep. 2006 Apr;26(2):113-29. doi: 10.1007/s10540-006-9011-2.

Abstract

A set of 10, chosen medicinal plants (some of them with a reputation as remedies for tuberculosis) has been investigated through Partitioned Iterated Function Systems-Semi Fractals with Angle (PIFS-SFA) coding, Lempel, Ziv, Welch with quantization and noise (LZW-QN) compression, and surface density statistics (f(alpha)-SDS) discrimination techniques. The final outcomes of this quantitative analysis were, firstly: the linear ordering of the plants in question accompanied by the hope that it reflects their medical significance, secondly: the mathematical representation of each of the plants, and thirdly: the impressive compression achieved, leading to remarkable computer memory saving, and still permitting successful pattern recognition i.e., proper identification of the plant from the compressed image.

摘要

通过分区迭代函数系统-带角度的半分形(PIFS-SFA)编码、带量化和噪声的莱姆佩尔-齐夫-韦尔奇(LZW-QN)压缩以及表面密度统计(f(α)-SDS)判别技术,对一组10种精选的药用植物(其中一些素有治疗结核病的声誉)进行了研究。该定量分析的最终结果如下:其一,相关植物的线性排序,同时希望这能反映它们的医学意义;其二,每种植物的数学表示;其三,实现了令人印象深刻的压缩,显著节省了计算机内存,并且仍能成功进行模式识别,即从压缩图像中正确识别植物。

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