Multi-Scale Aircraft Detection from Satellite Images
Yıl: 2021 Cilt: 14 Sayı: 1 Sayfa Aralığı: 322 - 330 Metin Dili: İngilizce DOI: 10.18185/erzifbed.891322 İndeks Tarihi: 02-03-2022
Multi-Scale Aircraft Detection from Satellite Images
Öz: Satellite image analysis is a research area in which many research studies are carried out for civil and military applications in the field of image processing. Satellite imagery has many applications including recognition, detection and classification of regions, buildings, roads, aircraft and other man-made objects. Among these, especially aircraft detection is strategically important for military applications, and forms the basis of this study. In the first phase of the study, a new dataset of aircrafts is created from Google Earth images to compensate the shortage of data set in this area. In the second stage, the detection of air vehicles was carried out using algorithms based on Convolutional Neural Network (CNN). Region-based Fully Convolutional Network (R-FCN), Single Shot Multi Box Detector (SSD) and Faster R-CNN methods are used for this process. The obtained accuracy rate for R-FCN, SSD and Faster R-CNN are 98.01%, 69.71% and 96.56%, respectively.
Anahtar Kelime: Uydu Görüntülerinden Çok Ölçekli Uçak Tespiti
Öz: Uydu görüntü analizi, görüntü işleme alanında sivil ve askeri uygulamalar için birçok çalışmanın yapıldığı geniş bir araştırma alanıdır. Uydu görüntüleri, bölgelerin, binaların, yolların, uçakların ve diğer insan yapımı nesnelerin tanınması, algılanması ve sınıflandırılması olmak üzere birçok uygulamada kullanılmaktadır. Uçak tespiti özellikle askeri uygulamalar için stratejik öneme sahiptir ve bu çalışmanın temelini oluşturmaktadır. Bu çalışmada uçak tespiti uygulamalarına yönelik veri seti eksikliğini telafi etmek için Google Earth görüntülerinden yeni bir uçak veri seti oluşturulmuştur. Hava araçlarının tespiti için Konvolüsyonel Sinir Ağlarına (CNNs) dayalı algoritmalar kullanılmıştır. Uçak tespitine yönelik yapılan deneylerde Bölge Tabanlı Tam Evrişimli Ağ (R-FCN), Tek Atışlı Çoklu Kutu Detektörü (SSD) ve Daha Hızlı R-CNN (Faster R-CNN) yöntemlerinin performansı karşılaştırılmıştır ve sırasıyla % 98.01,% 69.71 ve % 96.56 doğruluk oranları elde edilmiştir.
Anahtar Kelime: Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
- Anon. 2010. “DETECTING AIRCRAFT WITH A LOW RESOLUTION INFRARED SENSOR J ´ LTCI , UMR 5141 37-39 Rue Dareau DOTA MPSO Chemin de La Huni ` Ere 91761 Palaiseau.” 2475–77.
- Dalal, Navneet, and Bill Triggs. 2005. “Histograms of Oriented Gradients for Human Detection.” in Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005.
- Das, Subhodev, Bir Bhanu, Xing Wu, and R. Neil Braithwaite. 1994. “System for Aircraft Recognition in Perspective Aerial Images.” IEEE Workshop on Applications of Computer Vision - Proceedings 168–75. doi: 10.1109/acv.1994.341305.
- Deng, Zhipeng, Hao Sun, Shilin Zhou, Juanping Zhao, Lin Lei, and Huanxin Zou. 2018. “Multi-Scale Object Detection in Remote Sensing Imagery with Convolutional Neural Networks.” ISPRS Journal of Photogrammetry and Remote Sensing. doi: 10.1016/j.isprsjprs.2018.04.003.
- Felzenszwalb, Pedro, Ross Girshick, David Mcallester, and Deva Ramanan. 2010. “Object Detection with Discriminatively Trained Part-Based Models.” IEEE Transactions on Pattern Analysis and Machine Intelligence 32:1627–45. doi: 10.1109/TPAMI.2009.167.
- Girshick, Ross. 2015. “Fast R-CNN.” in Proceedings of the IEEE International Conference on Computer Vision.
- Girshick, Ross, Jeff Donahue, Trevor Darrell, and Jitendra Malik. 2014. “Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation.” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
- GitHub. 2017. “LabelImg.” Retrieved (https://github.com/tzutalin/labelImg). He, Kaiming, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep Residual Learning for Image Recognition.
- Hsieh, Jun-Wei, J. M. Chen, Chi-Hung Chuang, and K. C. Fan. 2005. “Aircraft Type Recognition in Satellite Images.” Vision, Image and Signal Processing, IEE Proceedings - 152:307–15. doi: 10.1049/ipvis:20049020. ImageNet. 2016. “ImageNet.” Retrieved (http://www.image-net.org/).
- Lin, Tsung Yi, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C. Lawrence Zitnick. 2014. “Microsoft COCO: Common Objects in Context.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 8693 LNCS(PART 5):740–55. doi: 10.1007/978-3- 319-10602-1_48.
- Liu, Wei, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng Yang Fu, and Alexander C. Berg. 2016. “SSD: Single Shot Multibox Detector.” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
- Networks, Region-based Fully Convolutional, and Jifeng Dai. 2016. “R-FCN : Object Detection Via.” ArXiv Preprint.
- Pandit, Tejas, Akshay Kapoor, Rishi Shah, and Rushi Bhuva. 2020. UNDERSTANDING INCEPTION NETWORK ARCHITECTURE FOR IMAGE CLASSIFICATION.
- Polat, M., H. M. A. Mohammed, E. A. Oral, and I. Y. Ozbek. 2019. “Aircraft Detection from Satellite Images Using ATA-Plane Data Set.” Pp. 1–4 in 2019 27th Signal Processing and Communications Applications Conference (SIU).
- Ren, Shaoqing, Kaiming He, Ross Girshick, and Jian Sun. 2017. “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.” IEEE Transactions on Pattern Analysis and Machine Intelligence. doi: 10.1109/TPAMI.2016.2577031.
- Simonyan, Karen, and Andrew Zisserman. 2014. “Very Deep Convolutional Networks for Large-Scale Image Recognition.” ArXiv 1409.1556.
- Viola, Paul, and Michael Jones. 2001. Rapid Object Detection Using a Boosted Cascade of Simple Features. Vol. 1.
- Xia, Gui Song, Xiang Bai, Jian Ding, Zhen Zhu, Serge Belongie, Jiebo Luo, Mihai Datcu, Marcello Pelillo, and Liangpei Zhang. 2018. “DOTA: A Large-Scale Dataset for Object Detection in Aerial Images.” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
- Xia, Gui Song, Jingwen Hu, Fan Hu, Baoguang Shi, Xiang Bai, Yanfei Zhong, Liangpei Zhang, and Xiaoqiang Lu. 2017. “AID: A Benchmark Data Set for Performance Evaluation of Aerial Scene Classification.” IEEE Transactions on Geoscience and Remote Sensing. doi: 10.1109/TGRS.2017.2685945.
| APA | Mohammed H, POLAT M, ALI TAHLIL A, OZBEK I (2021). Multi-Scale Aircraft Detection from Satellite Images. , 322 - 330. 10.18185/erzifbed.891322 |
| Chicago | Mohammed Hussein M. A.,POLAT MERVE,ALI TAHLIL Abdullatif,OZBEK IBRAHIM YÜCEL Multi-Scale Aircraft Detection from Satellite Images. (2021): 322 - 330. 10.18185/erzifbed.891322 |
| MLA | Mohammed Hussein M. A.,POLAT MERVE,ALI TAHLIL Abdullatif,OZBEK IBRAHIM YÜCEL Multi-Scale Aircraft Detection from Satellite Images. , 2021, ss.322 - 330. 10.18185/erzifbed.891322 |
| AMA | Mohammed H,POLAT M,ALI TAHLIL A,OZBEK I Multi-Scale Aircraft Detection from Satellite Images. . 2021; 322 - 330. 10.18185/erzifbed.891322 |
| Vancouver | Mohammed H,POLAT M,ALI TAHLIL A,OZBEK I Multi-Scale Aircraft Detection from Satellite Images. . 2021; 322 - 330. 10.18185/erzifbed.891322 |
| IEEE | Mohammed H,POLAT M,ALI TAHLIL A,OZBEK I "Multi-Scale Aircraft Detection from Satellite Images." , ss.322 - 330, 2021. 10.18185/erzifbed.891322 |
| ISNAD | Mohammed, Hussein M. A. vd. "Multi-Scale Aircraft Detection from Satellite Images". (2021), 322-330. https://doi.org/10.18185/erzifbed.891322 |
| APA | Mohammed H, POLAT M, ALI TAHLIL A, OZBEK I (2021). Multi-Scale Aircraft Detection from Satellite Images. Erzincan Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 14(1), 322 - 330. 10.18185/erzifbed.891322 |
| Chicago | Mohammed Hussein M. A.,POLAT MERVE,ALI TAHLIL Abdullatif,OZBEK IBRAHIM YÜCEL Multi-Scale Aircraft Detection from Satellite Images. Erzincan Üniversitesi Fen Bilimleri Enstitüsü Dergisi 14, no.1 (2021): 322 - 330. 10.18185/erzifbed.891322 |
| MLA | Mohammed Hussein M. A.,POLAT MERVE,ALI TAHLIL Abdullatif,OZBEK IBRAHIM YÜCEL Multi-Scale Aircraft Detection from Satellite Images. Erzincan Üniversitesi Fen Bilimleri Enstitüsü Dergisi, vol.14, no.1, 2021, ss.322 - 330. 10.18185/erzifbed.891322 |
| AMA | Mohammed H,POLAT M,ALI TAHLIL A,OZBEK I Multi-Scale Aircraft Detection from Satellite Images. Erzincan Üniversitesi Fen Bilimleri Enstitüsü Dergisi. 2021; 14(1): 322 - 330. 10.18185/erzifbed.891322 |
| Vancouver | Mohammed H,POLAT M,ALI TAHLIL A,OZBEK I Multi-Scale Aircraft Detection from Satellite Images. Erzincan Üniversitesi Fen Bilimleri Enstitüsü Dergisi. 2021; 14(1): 322 - 330. 10.18185/erzifbed.891322 |
| IEEE | Mohammed H,POLAT M,ALI TAHLIL A,OZBEK I "Multi-Scale Aircraft Detection from Satellite Images." Erzincan Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 14, ss.322 - 330, 2021. 10.18185/erzifbed.891322 |
| ISNAD | Mohammed, Hussein M. A. vd. "Multi-Scale Aircraft Detection from Satellite Images". Erzincan Üniversitesi Fen Bilimleri Enstitüsü Dergisi 14/1 (2021), 322-330. https://doi.org/10.18185/erzifbed.891322 |
