王璐;王雷欧;王东辉;

• 1:中国科学院声学研究所中科院水下航行器信息技术重点实验室
• 2:中国科学院大学

摘要(Abstract)：

对海洋资源开发的关键是实现对水下目标实时而准确的检测,但由于水介质的吸收以及悬浮粒子的散射作用,水下待测目标往往存在颜色失真、对比度低等复杂问题,这极不利于准确评估目标检测算法的性能。本文提出一种基于Faster-rcnn的水下目标检测算法,该算法以Faster-rcnn结构为主框架,将ResNet-101深度神经网络替代Faster-rcnn原本的VGG-16卷积神经网络作为特征提取和训练初始化的共享卷积网络,同时采用Water-Net网络对水下图像数据集进行增强处理,最后针对部分图像标签数据过少的问题采取了标签数据增强的方法。通过实验证明,数据集的增强性能有效提升检测算法的性能,且能满足实时检测的需求。

关键词(KeyWords)： 水下目标检测;Faster-rcnn模型;水下图像增强;Water-Net模型;数据增强

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金(编号：61801469);; 中国科学院声学研究所自主部署项目(编号：ZYTS202005)

作者(Author): 王璐;王雷欧;王东辉;

Email:

DOI:

参考文献(References)：

• [1] Jaffe J S.Computer modeling and the design of optimal underwater imaging systems[J].IEEE Journal of Oceanic Engineering,1990,15(2):101-111.
• [2] Girshick R,Donahue J,Darrell T,et al.Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation[C]//Proceedings of the IEEE conference on computer vision and pattern recogition,2014:580-587.
• [3] Redmon J,Divvala S,Girshick R,et al.You Only Look Once:Unified,Real-time Object Detection[C]//Proceedings of the IEEE conference on computer vision and pattern recognition.2016:779-788.
• [4] Liu W,Anguelov D,Erhan D,et al.SSD:Single Shot Multibox Detector[C]//European conference on computer vision.Springer,Cham,2016:21-37.
• [5] Redmon J,Farhadi A.YOLO9000:Better,Faster,Stronger[C]//IEEE Conference on Computer Vision & Pattern Recognition.IEEE,2017:6517-6525.
• [6]Jeong J,Park H,Kwak N.Enhancement of SSD by concatenating feature maps for object detection[C]//British Machine Vision Conference 2017.2017.
• [7] Law H,Deng J.CornerNet:Detecting Objects as Paired Keypoints[C]//European Conference on Computer Vision.Springer,Cham,2018:734-750.
• [8] He K,Zhang X,Ren S,et al.Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition[J].IEEE Transactions on Pattern Analysis & Machine Intelligence,2014,37(9):1904-16.
• [9] Girshick R.Fast r-cnn[C]//Proceedings of the IEEE International Conference on Computer Vision.2015:1440-1448.
• [10] Ren S,He K,Girshick R,et al.Faster r-cnn:Towards Real-time Object Detection with Region Proposal Networks[C]//Advances in Neural Information Processing systems.2015:91-99.
• [11] 多朵，洪缨，刘岩.一种应用于遥感图像分类的迁移学习算法[J].网络新媒体技术，2020,9(6):35-40.
• [12] Dai Jifeng,He Kaiming,Sun Jian.Instance-Aware semantic segmentation via multi-task network cascad[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.IEEE,2016:3150-3158.
• [13] He Kaiming,Zhang Xiangyu,Ren Shaoqing,et al.Deep residual learning for image recognition[C]//Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition.IEEE,2016:770-778.
• [14] Li C,Guo C,Ren W,et al.An Underwater Image Enhancement Benchmark Dataset and Beyond[J].IEEE Transactions on Image Processing,2019,29:4376-4389.
• [15] Ancuti C,Ancuti C.O.,Haber T.Enhancing underwater images and videos by fusion[C]//2012 IEEE conference on Computer vision and pattern recognition.IEEE,2012:81-88.
• [16] Li C Y,Guo C,J.R.Cong et al..Underwater image enhancement by dehazing with minimum information loss and histogram distribution prior[J].IEEE Transactions on Image Processing,2016,25(12):5664-5677.
• [17] Peng Y T,Cosman P C.Underwater Image Restoration Based on Image Blurriness and Light Absorption[J].IEEE Trans Image Process,2017,26(4):1579-1594.
• [18] Yan-Tsung,Peng,Keming,et al.Generalization of the Dark Channel Prior for Single Image Restoration[J].IEEE Transactions on Image Processing,2018,27(6):2856-2868.
• [19] Fu X,Zhang P,Huang Y,et al.A retinex-based enhancing approach for single underwater image[C]//2014 IEEE international conference on Image Process (ICIP).2014:4572-4576.
• [20] Zuiderveld K.Contrast Limited Adaptive Histogram Equalization-ScienceDirect[J].Graphics Gems,1994:474-485.