梯形高斯隶属度量化算法及在汽车图像库的仿真  

Trapezoidal Gaussian Membership Quantization Algorithm and Simulation in Vehicle Image Library

作　　者：胡明娣 霍艳艳 张孟斌 HU Ming-di;HUO Yan-yan;ZHANG Meng-bin(School of Communication and Information Engineering,Xi'an University of Posts and Telecommunications,Xi'an 710121,China;Key Laboratory of Electronic Information Application Technology for Scene Investigation,Ministry of Public Security,Xi'an 710121,China;International Joint Research Center for Wireless Communication and Information Processing,Xi'an 710121,China)

机构地区：[1]西安邮电大学通信与信息工程学院,陕西西安710121 [2]电子信息现场勘验应用技术公安部重点实验室,陕西西安710121 [3]陕西省无线通信与信息处理技术国际合作研究中心,陕西西安710121

出　　处：《模糊系统与数学》2018年第6期117-125,共9页Fuzzy Systems and Mathematics

基　　金：国家自然科学基金资助项目(61502386);陕西省科技厅国际合作项目(2018KW-050);陕西省教育厅科学研究计划项目(2013JK1074)

摘　　要：为了提高汽车图像检索的准确率,选择了一个合适的颜色空间和量化算法。首先本文自建了1000张汽车图像库,其次在HSV颜色空间提出了梯形高斯隶属度量化算法进行特征提取,最后通过欧式距离和加权距离进行相似度匹配。实验结果表明,该算法对汽车图像进行检索时的平均查准率要比梯形隶属度量化算法在欧氏距离进行相似度量时平均高出11.2个百分点;在加权距离进行相似度量时平均高出10.9个百分点。In order to improve the accuracy of image retrieval,a suitable color space and quantization algorithm are selected.First,a 1000 criminal vehicle image library is built in this paper.Secondly, the trapezoid Gauss membership quantization algorithm is proposed for feature extraction in HSV color space.Finally,the similarity is matched by the Euclidean distance and the weighted distance. The results show that the average precision of the algorithm is 11.2 percentage points higher than that of the trapezoid subordination algorithm at Euclidean distance,and the average height of the weighted distance is 10.9 percentage points higher than that of the weighted distance.

关 键 词：汽车图像 梯形高斯隶属度 欧式距离 加权距离 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]