Study of Cloud-Type Recognition Based on Multi-Class Features

摘要：

　　According to changeability of cloud, cloud-type recognition was primarily based on single-class feature in previous papers which was restricted to a certain degree.A set of features describing the color, texture as well as the shape features were extracted, then the shape and texture features combination methods were discussed.Here Gray-level co-occurrence matrix(GLCM) and Gabor wavelet transform based texture features and Zemikc moment based shape features were combined, then support vector machine (SVM) was employed to recognize cloud-type.Experimental results showed that the correct recognition rates of altocumulus, cirrus, clear, cumulus and stratus were improved significantly, with the average recognition rate of 88.6%, and clear sky and stratus”s recognition rate of 100%.

关键词： Feature Extraction Feature Combinations Cloud-Type Recognition Support Vector Machine (SVM)

作者: Ling YANG Zhong-ke WANG Jun WANG Wen-ting Cui

作者单位: College of Electronic Engineering,Chengdu University of Information Technology,Chengdu 610225,China College of Network Engineering,Chengdu University of Information Technology,Chengdu 610225,China

会议类型: 国内会议

会议名称: 第八届全国优秀青年气象科技工作者学术研讨会

会议地点: 江苏宜兴

会议语种:英文

页码: 1-7

在线出版日期: 2014-09-10（万方平台首次上网日期，不代表论文的发表时间）