Open Access

ARTICLE

Texture Feature Extraction Method for Ground Nephogram Based on Contourlet and the Power Spectrum Analysis Algorithm

by Xiaoying Chen, Shijun Zhao, Xiaolei Wang, Xuejin Sun, Jing Feng, Nan Ye

1 College of Mechanical & Electrical Engineering, Sanjiang University, Nanjing, China.
2 Institute of Meteorology and Oceanography, National University of Defense Technology, Nanjing, China.
3 Department of Civil Engineering, Monash Uniersity, Melbourne, Australia.

* Corresponding Author: Xiaoying Chen. Email: .

Computers, Materials & Continua 2019, 61(2), 861-875. https://doi.org/10.32604/cmc.2019.06230

Abstract

It is important to extract texture feature from the ground-base cloud image for cloud type automatic detection. In this paper, a new method is presented to capture the contour edge, texture and geometric structure of cloud images by using Contourlet and the power spectrum analysis algorithm. More abundant texture information is extracted. Cloud images can be obtained a multiscale and multidirection decomposition. The coefficient matrix from Contourlet transform of ground nephogram is calculated. The energy, mean and variance characteristics calculated from coefficient matrix are composed of the feature information. The frequency information of the data series from the feature vector values is obtained by the power spectrum analysis. Then Support Vector Machines (SVM) classifier is used to classify according to the frequency information of the trend graph of data series. It is shown that altocumulus and stratus with different texture frequencies can be effectively recognized and further subdivided the types of clouds.

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Citations