@inproceedings{32ddb3fe1e1d44cd97127be7aa862e4c,
title = "A hierarchical oil depot detector in high-resolution images with false detection control",
abstract = "Oil depot detection in high-resolution images is a challenging task due to the complicated background. This paper aims at further investigating this problem and presents an approach to detect oil depots in a hierarchical manner. Firstly, the Ellipse and Line Segment Detector (ELSD) which guards against false positives is applied to detect elliptical arcs in the image. Afterwards, the Histograms of Oriented Gradient (HOG) are extracted based on the elliptical arc candidates and input into the AdaBoost classifier in order to get the detection of oil tanks. Finally, the Depth-First-Search (DFS) is used to cluster the detection of oil tanks and determine the final oil depot area. Experimental results on real database indicate that the hierarchical algorithm is robust under complicated background and shows good performance against false positives.",
keywords = "AdaBoost, ELSD, HOG, Oil depot detection, graph search",
author = "Lu Zhang and Zhenwei Shi and Xinran Yu",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 7th International Congress on Image and Signal Processing, CISP 2014 ; Conference date: 14-10-2014 Through 16-10-2014",
year = "2014",
month = jan,
day = "6",
doi = "10.1109/CISP.2014.7003837",
language = "英语",
series = "Proceedings - 2014 7th International Congress on Image and Signal Processing, CISP 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "530--535",
editor = "Yi Wan and Jinguang Sun and Jingchang Nan and Quangui Zhang and Liangshan Shao and Lipo Wang",
booktitle = "Proceedings - 2014 7th International Congress on Image and Signal Processing, CISP 2014",
address = "美国",
}