|本期目录/Table of Contents|

[1]牟琦,周平.基于内容检索的硅藻细胞自动分类[J].浙江理工大学学报,2014,31-32(自科2):211-215.
 MU Qi,ZHOU Ping.Automatic Classification of Diatom Cells Based on Content Retrieval[J].Journal of Zhejiang Sci-Tech University,2014,31-32(自科2):211-215.
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基于内容检索的硅藻细胞自动分类()
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浙江理工大学学报[ISSN:1673-3851/CN:33-1338/TS]

卷:
第31-32卷
期数:
2014年自科2期
页码:
211-215
栏目:
(自科)生物与生命科学
出版日期:
2014-03-10

文章信息/Info

Title:
Automatic Classification of Diatom Cells Based on Content Retrieval
文章编号:
1673-3851 (2014) 02-0211-05
作者:
牟琦 周平
浙江理工大学信息学院, 杭州 310018
Author(s):
MU Qi ZHOU Ping
The School of Information Science and Technology, Zhejiang Sci-Tech University,Hangzhou 310018, China
关键词:
硅藻细胞分类 基于内容的图像检索 图像特征提取
分类号:
TP391.4
文献标志码:
A
摘要:
对硅藻细胞分类提出了一种基于内容的分类方法。该方法首先获取带外接圆的目标;然后,对其应用纹理主特征直方图,纹理变化度,纹理角特征3种方法提取出目标的特征向量;最后使用欧氏距离进行相似性度量。实验结果表明,该方法具有较好的分类准确率及召回率。

参考文献/References:

[1] Stoermer E F, Kreis Jr R G, Andresen N A. Checklist of diatoms from the Laurentian Great lakes. II[J]. Journal of Great Lakes Research, 1999, 25(3): 515-566.
[2] Jones V. Diatom Introduction[M]. Elias S A. Encyclopedia of Quaternary Science. Amsterdam: Elsevier Inc, 2007: 476-484.
[3] Smol J P, Stoermer E F. The Diatoms: Applications for the Environmental and Earth Sciences[M]. Cambridge: Cambridge University Press, 2004: 21-25.
[4] Songn Q, Wang G, Wang C. Automatic recommendation of classification algorithms based on dataset characteristics[J]. Pattern Recognition, 2012(45): 2672-2689.
[5] Dimitrovski I, Kocev D, Loskovska S, et al. Hierarchical classification of diatom images using ensembles of predictive clustering trees[J]. Ecological Informatics, 2012, 7(1): 19-29.
[6] Peng B, Zhang L, Zhang D. A survey of graph theoretical approaches to image segmentation[J]. Pattern Recognition, 2013(46): 1020-1038.
[7] Xie F, Bovik A C. Automatic segmentation of dermoscopy images using selfgenerating neural networks seeded by genetic algorithm[J]. Pattern Recognition, 2013(46): 1012-1019.
[8] Zhao F, Lin F, Seah H S. Binary SIPPER plankton image classification using random subspace[J]. Neurocomputing, 2010(73): 1853-1860.
[9] Chang L, Duarte M M, Sucar L E, et al. A Bayesian approach for object classification based on clusters of SIFT local features[J]. Expert Systems with Applications, 2012, 39(2): 1679-1686.
[10] Ranzato M, Taylor P E, House J M, et al. Automatic recognition of biological particles in microscopic images[J]. Pattern Recognition Letters, 2007, 28(1): 31-39.
[11] 韦娜, 耿国华, 周明全. 基于内容的图像检索系统性能评价[J]. 中国图象图形学报, 2004, 9(11): 1271-1275.
[12] 茹立云, 彭潇, 苏中, 等. 基于内容图像检索中的特征性能评价[J]. 计算机研究与发展, 2003, 40(11): 1566-1570.
[13] Wang X, Wang Z. A novel method for image retrieval based on structure elements descriptor[J]. Journal of Visual Communication and Image Representation, 2013, 24(1): 63-74.

备注/Memo

备注/Memo:
收稿日期: 2013-09-06
作者简介: 牟琦(1987-),男,山东青岛人,硕士研究生,主要从事图像处理方面的研究
通信作者: 周平,E-mail:zp@zstu.edu.cn
更新日期/Last Update: 2014-04-16