摘要
纹理是天气形势图的突出特征,有效地从天气形势图提取并表示其纹理是实现雾型实时在线预报的基础。基于此,提出一种改进的局部二值模式算法,通过调整局部二值模式(LBP)算子中二进制多项式的权重,实现其提取特定方向上纹理特征的目标。将江苏地区2010年—2017年500张浓雾天气形势图作为数据集,采用Chi统计法匹配测试数据与基准数据的相似度进行天气分类。实验结果表明,该算法的准确率、虚警率及临界成功指数分别为0.884、0.15和0.76,均优于LBP算法,具有较高的识别准确性与可靠性。
Texture is the salient feature of a weather situation map.Effectively extracting the textures from the weather situation map and representing them is the basis for real-time online prediction of fog pattern.To this end,this paper proposes an Improved Local Binary Pattern (ILBP) algorithm,which can extract texture features in a specific direction by adjusting the weight coefficients of binary polynomials in Local Binary Mode (LBP) operators.500 fog weather situation maps in Jiangsu Province from 2010 to 2017 are used as the dataset,and the similarities between the test data and the benchmark data are matched by Chi statistical method to classify the weather.Experimental results show that,the Probability of Detection (PoD),False Alarm Rate (FAR) and Critical Success Index (CSI) of the proposed algorithm are 0.884,0.15 and 0.76,respectively,which are better than those of the LBP algorithm.It proves that the proposed model has high accuracy and reliability.
作者
陈文兵
毛军杰
陈允杰
周林义
CHEN Wenbing;MAO Junjie;CHEN Yunjie;ZHOU Linyi(College of Mathematics and Statistics,Nanjing University of Information Science and Technology,Nanjing 210044,China;Key Laboratory of Transportation Meteorology,China Meteorological Administration,Nanjing 210009,China)
出处
《计算机工程》
CAS
CSCD
北大核心
2019年第5期199-204,209,共7页
Computer Engineering
基金
国家自然科学基金(61672291)
江苏省气象局北极阁基金(BJG201504)
关键词
改进的局部二值模式
纹理特征
特征提取
图像匹配
天气形势图
Improved Local Binary Pattern (ILBP)
texture feature
feature extraction
image matching
weather situation map