基于融合纹理特征的轮胎磨损程度检测方法  

Tire wear degree detection method based on fused texture features

作　　者：欧阳杰 张向文[1,2] 刘沛钊 陈凯文 Ouyang Jie;Zhang Xiangwen;Liu Peizhao;Chen Kaiwen(School of Electronic Engineering and Automation,Guilin University of Electronic Technology,Guilin 541004,China;Key Laboratory of Intelligence Integrated Automation in Guangxi Universities,Guilin 541004,China;Guangdong Hiway Integrated Circuit Technology Co.,Ltd.,Dongguan 523808,China)

机构地区：[1]桂林电子科技大学电子工程与自动化学院,桂林541004 [2]智能综合自动化广西高校重点实验室(桂林电子科技大学),桂林541004 [3]广东合微集成电路技术有限公司,东莞523808

出　　处：《电子测量技术》2024年第17期155-162,共8页Electronic Measurement Technology

基　　金：国家自然科学基金(62263006)项目资助。

摘　　要：轮胎磨损直接影响汽车行驶的安全性和稳定性,通过检测轮胎磨损程度可以及时发现轮胎异常状态并进行处理,提高汽车行驶的安全性。基于胎内传感器的轮胎磨损程度检测方法成本较高且安装过程繁琐,基于图像的检测方法则需要较多样本且检测准确性不高,本文提出一种基于融合纹理特征的轮胎磨损程度检测方法。采集5种不同磨损程度的25张轮胎图像构建训练集,每一张图像均匀裁剪为12张子图像,对每一张子图像通过中值滤波后分别提取灰度共生矩阵和局部二值模式特征,使用主成分分析和拼接融合方法获得融合特征。基于融合特征通过麻雀搜索算法和随机森林方法建立磨损程度分类器。最后,利用采集的225张不同磨损程度的轮胎图像进行测试。结果显示,平均检测准确率达到97.33%,相比单一特征及其他分类方法下准确率明显提高,可以应用于轮胎磨损程度的快速准确检测。The vehicle safety and stability during the driving process is directly influenced by the tire wear,and the vehicle safety can be improved by detecting the degree of tire wear to find and process the abnormal state of the tire timely.The tire wear degree can be detected with the sensor installed in the tire or the tire image directly.However,the sensor installed method has high cost and cumbersome installation process,and the image-based detection method requires more samples and the detection accuracy is not high.Therefore,a tire wear detection method based on fused texture features is proposed in this paper.The training set was constructed with 25 tire images of 5 different wear degrees,and each image was uniformly cropped into 12 sub-images,and the gray level co-occurrence matrix and local binary patterns features were extracted by median filtering,and the fusion features were obtained by principal component analysis and stitching fusion method.Then,the classifier was trained by sparrow search algorithm and the random forest method with the fusion features.Finally,the algorithm was tested with 225 acquired images of different degrees of tire wear.The results show that the average detection accuracy reaches 97.33%,which is significantly higher than that of a single feature and other classification methods,so,the proposed method can be used to detect the tire wear quickly and accurately.

关 键 词：轮胎磨损 纹理特征 主成分分析 麻雀搜索算法 随机森林 加权投票 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TN929.5[自动化与计算机技术—计算机科学与技术]