基于YOLOv3与分水岭的直升机桨叶欠曝光图像圆形标记点检测

doi:10.3969/j.issn.0255-8297.2020.06.007

应用科学学报 ›› 2020, Vol. 38 ›› Issue (6): 906-915.doi: 10.3969/j.issn.0255-8297.2020.06.007

• 信号与信息处理 • 上一篇

基于YOLOv3与分水岭的直升机桨叶欠曝光图像圆形标记点检测

张育斌¹, 熊邦书¹, 欧巧凤¹, 黄建萍², 陈垚锋²

1. 南昌航空大学江西省图像处理与模式识别重点实验室, 江西南昌 330063;
2. 中国直升机设计研究所直升机旋翼动力学实验室, 江西景德镇 333000

收稿日期:2020-01-15 发布日期:2020-12-08
通信作者: 熊邦书,教授,研究方向为模式识别、智能信号处理和图像处理.E-mail:xiongbs@126.com E-mail:xiongbs@126.com
基金资助:
国家自然科学基金（No.61866027）；江西省重点研发计划基金（No.20171BBE50013）；南昌航空大学研究生创新专项基金（No.YC2018021）资助

Circular Marker Detection of Under-Exposed Images of Helicopter Blades Based on YOLOv3 and Watershed

ZHANG Yubin¹, XIONG Bangshu¹, OU Qiaofeng¹, HUANG Jianping², CHEN Yaofeng²

1. Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition, Nanchang Hangkong University, Nanchang 330063, Jiangxi, China;
2. Science and Technology on Rotorcraft Aeromechanics Laboratory, China Helicopter Research and Development Institute, Jingdezhen 333000, Jiangxi, China

Received:2020-01-15 Published:2020-12-08

摘要/Abstract

摘要： 针对现有的直升机桨叶欠曝光图像中圆形标记点检测方法存在自适应能力不强、速度慢、精度不高的问题，提出了基于YOLOv3（you only look once）与分水岭的直升机桨叶欠曝光图像圆形标记点检测方法.首先，将采集的真实桨叶欠曝光图像中的圆形标记点进行标注后，制作成数据集，并训练YOLOv3网络；其次，用训练好的YOLOv3网络检测出圆形标记点区域；再次，改进传统分水岭标记提取方式，采用多线程技术并行在各圆形标记点区域内进行分水岭变换，得到圆形标记点边缘检测结果；最后，采用最小二乘圆拟合和奇异点去除法实现圆形标记点的精确定位.研究者通过对多幅欠曝光桨叶图像中圆形标记点进行检测实验，验证了该方法具有自适应能力强、速度快、精度高的优点，并已将其用于直升机桨叶欠曝光图像圆形标记点的检测.

关键词: 欠曝光图像, 圆形标记点检测, YOLOv3, 分水岭变换

Abstract: A method of circular marker detection in under-exposed helicopter blade images based on YOLOv3 (you only look once) and watershed algorithm is proposed, aiming to improve detection adaptability, speed up the detection and obtain accurate position of circular markers. Firstly, the real under-exposed blade images are labeled for dataset making, on which the YOLOv3 network is trained. Secondly, the circular marker regions in blade images from testing dataset are detected by the trained YOLOv3 network. Thirdly, the traditional watershed marker detection method is improved, and the circular marker regions are used for the watershed transformation by the multi-threading technology in parallel, and the edge detection results of the circular marker are obtained. Finally, the circular markers are accurately located by the least square circle fitting and the method of removing the singular points. The proposed method is proved to be adaptable, fast and accurate by a number of experiments in many under-exposed helicopter blade images, and has been applied to circular marker detection in under-exposed helicopter blade images.

Key words: under-exposed image, circular marker detection, YOLOv3, watershed transformation

中图分类号:

TP391.41

张育斌, 熊邦书, 欧巧凤, 黄建萍, 陈垚锋. 基于YOLOv3与分水岭的直升机桨叶欠曝光图像圆形标记点检测[J]. 应用科学学报, 2020, 38(6): 906-915.

ZHANG Yubin, XIONG Bangshu, OU Qiaofeng, HUANG Jianping, CHEN Yaofeng. Circular Marker Detection of Under-Exposed Images of Helicopter Blades Based on YOLOv3 and Watershed[J]. Journal of Applied Sciences, 2020, 38(6): 906-915.

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基于YOLOv3与分水岭的直升机桨叶欠曝光图像圆形标记点检测

Circular Marker Detection of Under-Exposed Images of Helicopter Blades Based on YOLOv3 and Watershed

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