[1]夏德深,金盛,王健.基于分数维与灰度梯度共生矩阵的气象云图识别(Ⅱ)——灰度梯度共生矩阵对纹理统计特征的描述[J].南京理工大学学报(自然科学版),1999,(04):289-292.
 XiaDeshen JinSheng WangJian.Fractal Dimension and GGCM Meteorology Cloud Pictures Recognition[J].Journal of Nanjing University of Science and Technology,1999,(04):289-292.
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基于分数维与灰度梯度共生矩阵的气象云图识别(Ⅱ)——灰度梯度共生矩阵对纹理统计特征的描述()
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
期数:
1999年04期
页码:
289-292
栏目:
出版日期:
1999-08-30

文章信息/Info

Title:
Fractal Dimension and GGCM Meteorology Cloud Pictures Recognition
作者:
夏德深金盛王健
南京理工大学计算机科学与技术系, 南京210094
Author(s):
XiaDeshen JinSheng WangJian
Department of Computer Science and Technology,NUST,Nanjing 210094
关键词:
卫星云图 模式识别 图像处理 灰度梯度共生矩阵 纹理分析
Keywords:
satellite cloud pictures pat tern recog nit ion image processing gray gradient cooccurence matrix tex ture analysis
分类号:
TP391.41
摘要:
图像的分数维特征描述了纹理的复杂度和粗糙度。图像的灰度梯度信息则检出了图像中灰度跳变的部分,将图像的梯度信息加进灰度共生矩阵,则使得共生矩阵更能包含图像的纹理基元及其排列的信息。将4 种基本云类(卷云、积雨云、积云和层云)的分数维和灰度梯度共生矩阵(GGCM)的二次统计特征结合起来,对云类进行分类与识别。样本的试验表明,分数维和灰度梯度共生矩阵的二次统计特征结合起来,气象云图能有效地识别。
Abstract:
The image fractal dimension feature describes the complex ity and the roughness of texture. The image g ray gradient checks up the skip part of image g ray. Combining the grad-i ent informat ion w ith gray level co-occurence matrix, it w ill be bet ter to include the information of tex ture elements and its arrangement . Combined the fractal dimension w ith the 2-order stat istical features of Gray Gradient Co-occurence Mat rix ( GGCM) of 4 kinds of basic clouds pictures ( Cirrus, Cumulus, Cumulonimbus and Layer Cloud) , the clouds are classif ied and recognized. T he samples experiments show ed that with the combination of the fractal dimension and the 2-order statistical features of GGCM, the meteorological cloud pictures can be recog nized effect ively.

参考文献/References:

1 Portille-Garcia J, T rueba- Santander I, de Mig ue-l Vela G. Efficient multispectral texture segmentation using multivariate statistics. IEEE Pr oceedings, Vision, Imag e, and Signal Processing , 1998,145( 5) : 357~ 364
2 Bouman C A. Multi resolut ion segmentatio n of textured images. IEEE PAMI, 1991, 6: 99~ 113
3 Anderson T W. An I ntroduction to Multiv ar iate Statistical Analysis. New Yorks: Jo hn Wiley &Sons, 1984
4 Fan Z, Cohen F S. Textured image segmentat ion as a multiple hypo thesis test. IEEE Transaction,Circuits System, 1998, cs- 35: 691~ 702

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备注/Memo

备注/Memo:
夏德深 男 56 岁 教授
更新日期/Last Update: 2013-03-29