{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:31:48Z","timestamp":1760236308278,"version":"build-2065373602"},"reference-count":30,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2021,11,18]],"date-time":"2021-11-18T00:00:00Z","timestamp":1637193600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2016YFF0202700"],"award-info":[{"award-number":["2016YFF0202700"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61991420"],"award-info":[{"award-number":["61991420"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Object localization is an important application of remote sensing images and the basis of information extraction. The acquired accuracy is the key factor to improve the accuracy of object structure information inversion. The floating roof oil tank is a typical cylindrical artificial object, and its top cover fluctuates up and down with the change in oil storage. Taking the oil tank as an example, this study explores the localization by combining the traditional feature parameter method and convolutional neural networks (CNNs). In this study, an improved fast radial symmetry transform (FRST) algorithm called fast gradient modulus radial symmetry transform (FGMRST) is proposed and an approach based on FGMRST combined with CNN is proposed. It effectively adds the priori of circle features to the calculation process. Compared with only using CNN, it achieves higher precision localization with fewer network layers. The experimental results based on SkySat data show that the method can effectively improve the calculation accuracy and efficiency of the same order of magnitude network, and by increasing the network depth, the accuracy still has a significant improvement.<\/jats:p>","DOI":"10.3390\/rs13224646","type":"journal-article","created":{"date-parts":[[2021,11,19]],"date-time":"2021-11-19T02:43:09Z","timestamp":1637289789000},"page":"4646","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Accurate Localization of Oil Tanks in Remote Sensing Images via FGMRST-Based CNN"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3690-0492","authenticated-orcid":false,"given":"Han","family":"Jiang","sequence":"first","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100194, China"},{"name":"Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Yueting","family":"Zhang","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100194, China"},{"name":"Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China"}]},{"given":"Jiayi","family":"Guo","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100194, China"}]},{"given":"Fangfang","family":"Li","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100194, China"}]},{"given":"Yuxin","family":"Hu","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100194, China"}]},{"given":"Bin","family":"Lei","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100194, China"}]},{"given":"Chibiao","family":"Ding","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100194, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,18]]},"reference":[{"key":"ref_1","first-page":"57","article-title":"Review of change detection methods based on Remote Sensing Images","volume":"24","author":"Meng","year":"2012","journal-title":"Technol. Innov. Appl."},{"key":"ref_2","first-page":"180","article-title":"Application of Deep Learning in Target Recognition and Position in Remote Sensing Images","volume":"34","author":"Sui","year":"2019","journal-title":"Technol. Innov. Appl."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1117\/1.JRS.8.083689","article-title":"Oil tank detection in synthetic aperture radar images based on quasi-circular shadow and highlighting arcs","volume":"8","author":"Xu","year":"2014","journal-title":"J. Appl. Remote Sens."},{"key":"ref_4","unstructured":"Yu, S.T. (2019). Research on Oil Tank Volume Extraction Based on High Resolution Remote Sensing Image. [Master\u2019s Thesis, Dalian Maritime University]."},{"key":"ref_5","first-page":"4","article-title":"A Practical Measurement for Oil Tank Storage","volume":"1","author":"Ding","year":"2001","journal-title":"J. Lanzhou Petrochem. Polytech."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1145\/361237.361242","article-title":"Use of the Hough transformation to detect lines and curves in pictures","volume":"15","author":"Duda","year":"1972","journal-title":"Commun. ACM"},{"key":"ref_7","unstructured":"Shin, B.G., Park, S.Y., and Lee, J.J. (2007, January 17\u201320). Fast and robust template matching algorithm in noisy image. Proceedings of the International Conference on Control, Automation and Systems, Seoul, Korea."},{"key":"ref_8","first-page":"503","article-title":"Oil Tank Extraction from Remote Sensing Images Based on Visual Attention Mechanism and Hough Transform","volume":"16","author":"Wu","year":"2015","journal-title":"J. Inf. Eng. Univ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"66","DOI":"10.3724\/SP.J.1146.2010.00112","article-title":"Oil Depots Recognition Based on Improved Hough Transform and Graph Search","volume":"33","author":"Han","year":"2011","journal-title":"J. Electron. Inf. Technol."},{"key":"ref_10","first-page":"154","article-title":"A Saliency Map Segmentation Oil Tank Detection Method in Remote Sensing Image","volume":"28","author":"Cai","year":"2015","journal-title":"Electron. Sci. Technol."},{"key":"ref_11","first-page":"1298","article-title":"An Automatic Oil Tank Detection Algorithm Based on Remote Sensing Image","volume":"27","author":"Zhang","year":"2006","journal-title":"J. Astronaut."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","article-title":"A Fast Learning Algorithm for Deep Belief nets","volume":"18","author":"Hinton","year":"2006","journal-title":"Neural. Comput."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"Lecun","year":"2015","journal-title":"Nature"},{"key":"ref_14","first-page":"2806","article-title":"Overview of deep learning","volume":"29","author":"Sun","year":"2012","journal-title":"Appl. Res. Comput."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1162\/neco.1989.1.4.541","article-title":"Backpropagation Applied to Handwritten Zip Code Recognition","volume":"1","author":"Lecun","year":"1989","journal-title":"Neural. Comput."},{"key":"ref_16","unstructured":"Krizhevsky, A., Sutskever, I., and Hinton, G. (2012, January 3\u20138). ImageNet Classification with Deep Convolutional Neural Networks. Proceedings of the Annual Conference on Neural Information Processing Systems, Lake Tahoe, NV, USA."},{"key":"ref_17","unstructured":"(2020, October 01). Deep Residual Learning for Image Recognition. Available online: https:\/\/arxiv.org\/pdf\/1512.03385.pdf."},{"key":"ref_18","first-page":"727","article-title":"Oil Tank Detection from Remote Sensing Images based on Deep Convolutional Neural Network","volume":"34","author":"Wang","year":"2019","journal-title":"Remote Sens. Technol. Appl."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"959","DOI":"10.1109\/TPAMI.2003.1217601","article-title":"Fast radial symmetry for detecting points of interest","volume":"25","author":"Loy","year":"2003","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell"},{"key":"ref_20","first-page":"82","article-title":"Sky Sat","volume":"7","author":"Gong","year":"2016","journal-title":"Satell. Appl."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1007\/BF01418978","article-title":"Context-free attentional operators: The generalized symmetry transform","volume":"14","author":"Reisfeld","year":"1995","journal-title":"Int. J. Comput. Vis."},{"key":"ref_22","first-page":"1","article-title":"Extraction of Facial Features for Recognition using Neural Networks","volume":"19","author":"Intrator","year":"1995","journal-title":"Acta Obs. Gynecol Scand."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1006\/cviu.1997.0640","article-title":"Preprocessing of Face Images: Detection of Features and Pose Normalization","volume":"71","author":"Reisfeld","year":"1998","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1006\/rtim.1996.0057","article-title":"Real-Time Attention for Robotic Vision","volume":"3","author":"Sela","year":"1997","journal-title":"Real-Time Imaging"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1145\/360666.360677","article-title":"Finding Circles by an Array of Accumulators","volume":"18","author":"Kimme","year":"1975","journal-title":"Commun. ACM"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1109\/TSMC.1981.4308652","article-title":"The Detection and Segmentation of Blobs in Infrared Images","volume":"11","author":"Minor","year":"1981","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1347","DOI":"10.1109\/LGRS.2015.2401600","article-title":"Circular Oil Tank Detection from Panchromatic Satellite Images: A New Automated Approach","volume":"12","author":"Ok","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1109\/TPAMI.2015.2462355","article-title":"Automatic Shadow Detection and Removal from a Single Image","volume":"38","author":"Khan","year":"2016","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2956","DOI":"10.1109\/TPAMI.2012.214","article-title":"Paired Regions for Shadow Detection and Removal","volume":"35","author":"Guo","year":"2013","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Guo, R.Q., Dai, Q.Y., and Hoiem, D. (2011, January 20\u201325). Single-image shadow detection and removal using paired regions. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Colorado Springs, CO, USA.","DOI":"10.1109\/CVPR.2011.5995725"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/22\/4646\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:32:18Z","timestamp":1760167938000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/22\/4646"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,18]]},"references-count":30,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["rs13224646"],"URL":"https:\/\/doi.org\/10.3390\/rs13224646","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2021,11,18]]}}}