Research on Vehicle identification based on high resolution satellite remote sensing image

被引:6
作者
Guo, Dudu [1 ,2 ]
Zhu, Shunying [1 ]
Wei, Ji'ao [2 ]
机构
[1] Wuhan Univ Technol, Wuhan 430000, Hubei, Peoples R China
[2] Xinjiang Univ, Urumqi 830047, Peoples R China
来源
2019 INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION, BIG DATA & SMART CITY (ICITBS) | 2019年
关键词
Vehicle identification; High resolution satellite; Framework of vehicle detection; Bright color vehicles; Dark color vehicles;
D O I
10.1109/ICITBS.2019.00024
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Traditional traffic information acquisition methods had many limitations, so the acquisition of road traffic information from high-resolution satellite images had become a research hotspot in intelligent traffic system. In this paper, the object oriented classification method is used to establish the vehicle detection and processing process of high resolution satellite image. First, the high resolution satellite image was processed by median filtering and denoising, and the enhancement of vehicle information in remote sensing images was realized by using the stretch of gray histogram. Secondly, the image was segmented to the optimal scale, and the optimal segmentation scale was determined by the method of the maximum average area of the vehicle. Then according to different color characteristics of vehicles with dark establish a separate classification rule set, based on the object-oriented classification of vehicle classification, by extracting feature threshold classification more bright color vehicles, using relationship between classes of vehicles using fuzzy classification method to extract the dark color vehicles, finally formed a high-resolution satellite remote sensing overall framework of vehicle detection.
引用
收藏
页码:62 / 65
页数:4
相关论文
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