基于改进Faster RCNN的水接触角测量方法  

Water Contact Angle Calculation Method Based on Faster RCNN

作　　者：王慧 王军[1,2] 曹召良 Wang Hui;Wang Jun;Cao Zhaoliang(School of Physical Science and Technology,Suzhou University of Science and Technology,Suzhou 215009,Jiangsu,China;State Key Laboratory of Applied Optics,Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences,Changchun 130033,Jilin,China)

机构地区：[1]苏州科技大学物理科学与技术学院,江苏苏州215009 [2]中国科学院长春光学精密机械与物理研究所应用光学国家重点实验室,吉林长春130033

出　　处：《激光与光电子学进展》2024年第8期182-191,共10页Laser & Optoelectronics Progress

基　　金：“十四五”江苏省重点学科资助(2021135);中国航天科技集团公司第八研究院产学合作基金资助(SAST2020-025)。

摘　　要：针对传统水接触角测量过程需要人工干预,导致测量结果精度低、可复现性差等问题,提出一种基于改进Faster RCNN的水接触角测量方法。首先,把Faster RCNN骨干网络VGG16替换为ResNet101,在其残差块末尾处添加注意力机制模型convolutional block attention module(CBAM),增强网络提取特征的能力;其次,融入特征金字塔网络(FPN),充分提取不同尺度下的特征信息,此外,引入Focal损失函数来解决正负类样本不均衡的问题;最后,对定位到的水滴进行边缘检测和角点提取,再利用迭代重加权最小二乘法(IRLS)拟合椭圆轮廓计算水接触角。实验结果表明,改进后的Faster RCNN目标检测算法与原算法相比,平均精度均值提高10.794%,速度提升11 frame/s,水接触角测量结果平均标准偏差为0.109°。A water contact angle measurement method based on the improved Faster RCNN is proposed to address the issues of low accuracy and poor reproducibility caused by manual intervention in traditional water contact angle measurement processes.First,the Faster RCNN backbone network VGG16 was replaced with ResNet101,and the attention mechanism model convolutional block attention module(CBAM)was added at the end of its residual block to enhance the network’s ability to extract features.Second,the feature pyramid network(FPN)was incorporated to fully extract feature information at different scales,and the Focal loss function was introduced to solve the problem of imbalanced positive and negative class samples.Finally,edge detection and corner extraction were performed on the located water droplets,and then the iterative reweighted least squares(IRLS)method was used to fit the elliptical contour to calculate the contact angle angle.The experimental results show that the improved Faster RCNN object detection algorithm improves mean average precision by 10.794%and speed by 11 frame/s over the original algorithm.The average standard deviation of contact angle angle measurements is 0.109°.

关 键 词：图像处理 水接触角 特征金字塔网络 注意力机制 Faster RCNN 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]