Classification of silver halide microcrystals via K-NN clustering of their shape descriptors

被引：0

作者：

Kindratenko, VV ^{[1
]}

Treiger, BA ^{[1
]}

VanEspen, PJM ^{[1
]}

机构：

[1] UNIV INSTELLING ANTWERP,DEPT CHEM,MICRO & TRACE ANAL CTR,B-2610 WILRIJK,BELGIUM

来源：

JOURNAL OF CHEMOMETRICS | 1997年 / 11卷 / 02期

关键词：

shape description; image processing; K-NN clustering;

D O I：

10.1002/(SICI)1099-128X(199703)11:2<131::AID-CEM460>3.0.CO;2-6

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A method for the classification of tabular grain silver halide microcrystals according to their shape is presented, Various approaches of shape analysis and recognition and their applicability for the given problem are discussed. Shape descriptors obtained from Fourier power spectra are used to describe the shape of microcrystals. The classification of the shapes is based on nearest neighborhood algorithms. Results of the classification by four different algorithms are compared. The fuzzy four-nearest-neighbor classifier was found to be the most appropriate one. (C) 1997 by John Wiley & Sons, Ltd.

引用

页码：131 / 139

页数：9

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