重庆科技学院学报（自然科学版）2024，Vol.26Issue(3)：93-98,110,7.DOI:10.19406/j.issn.1673-1980.2024.03.015
面向高机动目标检测的激光雷达探测图像分角域识别方法
A Corner Domain Recognition Method of Lidar Detection Images for High Maneuvering Target Detection
摘要
Abstract
The high-speed movement and rapid transformation of motion modes can easily cause target blurring,making it difficult to accurately determine the contour,shape,and position of the target.To this end,a corner do-main recognition method for lidar detection images targeting high maneuverability target detection is proposed.First-ly,by detecting abnormal pixel distance within the neighborhood range,noise and abnormal signals in the LiDAR detection image are removed;Then,L-R algorithm is used to solve the image blur problem caused by high-speed moving targets;Finally,the image is segmented into different angle domains using an adaptive corner domain parti-tioning method based on mutual information,and high-precision target recognition is performed in each angle do-main through convolutional neural networks to achieve high maneuverability target lidar detection.The experimental results show that this method can effectively remove the blurring phenomenon of lidar detection images caused by high maneuvering targets;Compared to other traditional methods,this method has higher target recognition rate and overall average accuracy,lower average time consumption for single image recognition,and has good recognition performance.关键词
激光雷达探测图像/高机动目标/分角域/互信息/卷积神经网络Key words
lidar detection images/high maneuvering targets/angular domain/mutual information/convolutional neural network分类
信息技术与安全科学引用本文复制引用
韩钰,王磊,郑金亮,王紫玉..面向高机动目标检测的激光雷达探测图像分角域识别方法[J].重庆科技学院学报（自然科学版）,2024,26(3):93-98,110,7.基金项目
2022年度安徽省高等学校科学研究项目(自然科学类)重点项目"基于PP-YOLO的目标表面瑕疵检测研究"(2022AH053061) （自然科学类）
