Systems Engineering and Electronics ›› 2022, Vol. 44 ›› Issue (6): 1772-1781.doi: 10.12305/j.issn.1001-506X.2022.06.02
• Electronic Technology • Previous Articles Next Articles
Runlin LI, Huanxin ZOU*, Xu CAO, Fei CHENG, Shitian HE, Meilin LI
Received:
2021-06-25
Online:
2022-05-30
Published:
2022-05-30
Contact:
Huanxin ZOU
CLC Number:
Runlin LI, Huanxin ZOU, Xu CAO, Fei CHENG, Shitian HE, Meilin LI. Multi-direction remote sensing ship detection based on center point and semantic information[J]. Systems Engineering and Electronics, 2022, 44(6): 1772-1781.
Table 1
Comparison of different ship detection methods on HRSC2016 dataset"
性能参数 | 舰船目标检测方法 | |||||||
R2CNN | RR-CNN | RRPN | RNet-H | RRD | RoI-T | RSI-C | ||
骨干网络 | R101 | VGG16 | R101 | R101 | VGG16 | R101 | R101 | |
输入尺寸 | 800×800 | - | 800×800 | 800×800 | 384×384 | 512×800 | 512×512 | |
检测速度/FPS | 5 | - | 1.5 | 14 | - | 6 | 17.8 | |
AP/% | 73.07 | 75.7 | 79.08 | 82.89 | 84.3 | 86.2 | 88.31 |
1 |
王伦文, 冯彦卿, 张孟伯. 光学遥感图像目标检测方法[J]. 系统工程与电子技术, 2019, 41 (10): 2163- 2169.
doi: 10.3969/j.issn.1001-506X.2019.10.02 |
WANG L W , FENG Y Q , ZHANG M B . Target detection method for optical remote sensing imagery[J]. Systems Engineering and Electronics, 2019, 41 (10): 2163- 2169.
doi: 10.3969/j.issn.1001-506X.2019.10.02 |
|
2 | MA L, GUO J, WANG Y, et al. Ship detection by salient convex boundaries[C]//Proc. of the 3rd International Congress on Image and Signal Processing, 2010: 202-205. |
3 |
储昭亮, 王庆华, 陈海林, 等. 基于极小误差阈值分割的舰船自动检测方法[J]. 计算机工程, 2007, (11): 239- 241.239-241, 269
doi: 10.3969/j.issn.1000-3428.2007.11.086 |
CHU Z L , WANG Q H , CHEN H L , et al. Ship auto detection method based on minimum error threshold segmentation[J]. Computer Engineering, 2007, (11): 239- 241.239-241, 269
doi: 10.3969/j.issn.1000-3428.2007.11.086 |
|
4 | 胡俊华, 徐守时, 陈海林, 等. 基于局部自相似性的遥感图像港口舰船检测[J]. 中国图象图形学报, 2009, 14 (4): 591- 597. |
HU J H , XU S S , CHEN H L , et al. Detection of ships in harbor in remote sensing image based on local self-similarity[J]. Journal of Image and Graphics, 2009, 14 (4): 591- 597. | |
5 |
尤晓建, 徐守时, 侯蕾. 基于特征融合的可见光图像舰船检测新方法[J]. 计算机工程与应用, 2005, (19): 199- 202.
doi: 10.3321/j.issn:1002-8331.2005.19.058 |
YOU X J , XU S S , HOU L . A new method for ship detection based on feature fusion in optical image[J]. Computer Engineering and Applications, 2005, (19): 199- 202.
doi: 10.3321/j.issn:1002-8331.2005.19.058 |
|
6 |
GAO L N , BI F K , YANG J . Visual attention based model for target detection in large-field images[J]. Journal of Systems Engineering and Electronics, 2011, 22 (1): 150- 156.
doi: 10.3969/j.issn.1004-4132.2011.01.020 |
7 | 肖利平, 曹炬, 高晓颖. 复杂海地背景下的舰船目标检测[J]. 光电工程, 2007, (6): 6- 10. |
XIAO L P , CAO J , GAO X Y . Detection for ship targets in complicated background of sea and land[J]. Opto-E1ectronic Engineering, 2007, (6): 6- 10. | |
8 | 蒋李兵. 基于高分辨光学遥感图像的舰船目标检测方法研究[D]. 长沙: 国防科学技术大学, 2007. |
JIANG L B. Research on the ship target detection in high spatial resolution optical remote sensing image[D]. Changsha: National University of Defense Technology, 2007. | |
9 | JING Y Y, ZHU X Y, WANG X B, et al. R2CNN: rotational region CNN for orientation robust scene text detection[J]. arXiv preprint arXiv: 1706.09579, 2017. |
10 | LIU Z K, HU J G, WENG L B, et al. Rotated region based CNN for ship detection[C]//Proc. of the IEEE International Conference on Image Processing, 2017: 900-904. |
11 |
MA J Q , SHAO W Y , YE H , et al. Arbitrary-oriented scene text detection via rotation proposals[J]. IEEE Trans.on Multimedia, 2018, 20 (11): 3111- 3122.
doi: 10.1109/TMM.2018.2818020 |
12 | DING J, XUE N, LONG Y, et al. Learning RoI transformer for oriented target detection in aerial images[C]//Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019: 2849-2858. |
13 | REN S Q , HE K M , GIRSHICK R , et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. Advances in Neural Information Processing Systems, 2015, 28, 91- 99. |
14 | 孙嘉赤, 邹焕新, 邓志鹏, 等. 基于级联卷积神经网络的港口多方向舰船检测与分类[J]. 系统工程与电子技术, 2020, 42 (9): 1903- 1910. |
SUN J C , ZOU H X , DENG Z P , et al. Oriented inshore ship detection and classification based on cascade RCNN[J]. Systems Engineering and Electronics, 2020, 42 (9): 1903- 1910. | |
15 | CAI Z, VASCONCELOS N. Cascade R-CNN: delving into high quality object detection[C]//Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018: 6154-6162. |
16 | YANG X, LIU Q Q, YAN J C, et al. R3det: refined single-stage detector with feature refinement for rotating object[EB/OL]. [2021-06-25]. https://arxiv.org/abs/1908.05612. |
17 | LIN T Y, GOYAL P, GIRSHICK R, et al. Focal loss for dense object detection[C]//Proc. of the IEEE International Conference on Computer Vision, 2017: 2980-2988. |
18 | LIAO M H, ZHU Z, SHI B G, et al. Rotation-sensitive regression for oriented scene text detection[C]//Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recog-nition, 2018: 5909-5918. |
19 | LIU W, ANGUELOV D, ERHAN D, et al. SSD: single shot multibox detector[C]//Proc. of the European Conference on Computer Vision, 2016: 21-37. |
20 | 张筱晗, 姚力波, 吕亚飞, 等. 基于中心点的遥感图像多方向舰船目标检测[J]. 光子学报, 2020, 49 (4): 210- 218. |
ZHANG X H , YAO L B , LYU Y F , et al. Center based model for arbitrary-oriented ship detection in remote sensing images[J]. Acta Photonica Sinica, 2020, 49 (4): 0410005. | |
21 | LI L H , ZHOU Z Q , WANG B , et al. A novel CNN-based method for accurate ship detection in HR optical remote sensing images via rotated bounding box[J]. IEEE Trans.on Geoscience and Remote Sensing, 2020, 59 (1): 689- 699. |
22 |
LIU Q W , XIANG X Q , YANG Z , et al. Arbitrary direction ship detection in remote-sensing images based on multitask learning and multiregion feature fusion[J]. IEEE Trans.on Geoscience and Remote Sensing, 2021, 59 (2): 1553- 1564.
doi: 10.1109/TGRS.2020.3002850 |
23 |
LI H , DENG L B , YANG C , et al. Enhanced YOLO v3 tiny network for real-time ship detection from visual image[J]. IEEE Access, 2021, 9, 16692- 16706.
doi: 10.1109/ACCESS.2021.3053956 |
24 |
WU Y F , ZHAO W , ZHANG R F , et al. AMR-Net: arbitrary-oriented ship detection using attention module, multi-scale feature fusion and rotation pseudo-label[J]. IEEE Access, 2021, 9, 68208- 68222.
doi: 10.1109/ACCESS.2021.3075857 |
25 | CHEN J J , XIE F Y , LU Y Y , et al. Finding arbitrary-oriented ships from remote sensing images using corner detection[J]. IEEE Geoscience and Remote Sensing Letters, 2019, 17 (10): 1712- 1716. |
26 | LAW H, DENG J. CornerNet: detecting objects as paired keypoints[C]//Proc. of the European Conference on Computer Vision, 2018: 734-750. |
27 | ZHOU X, WANG D, KRAHENBUHL P. Objects as points[EB/OL]. [2021-06-25]. https://arxiv.org/abs/1904.07850. |
28 |
ZHOU L , WEI H R , LI H , et al. Arbitrary-oriented object detection in remote sensing images based on polar coordinates[J]. IEEE Access, 2020, 8, 223373- 223384.
doi: 10.1109/ACCESS.2020.3041025 |
29 | LIU Z K, YUAN L, WENG L B, et al. A high resolution optical satellite image dataset for ship recognition and some new baselines[C]//Proc. of the International Conference on Pattern Recognition Applications and Methods, 2017, 2: 324-331. |
30 | EVERINGHAM M , WINN J . The pascal visual object classes challenge 2012 (voc2012) development kit[J]. Pattern Analysis, Statistical Modelling and Computational Learning, 2011, 8, 5. |
31 | CHEN K, PANG J M, WANG J Q, et al. Hybrid task cascade for instance segmentation[C]//Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019: 4974-4983. |
32 | WOO S, PARK J, LEE J Y, et al. Cbam: convolutional block attention module[C]//Proc. of the European Conference on Computer Vision, 2018: 3-19. |
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