Detecting Cars in VHR SAR Images with a Fuzzy Semantic Algorithm

被引：0
|
作者：
Huang Y. [1 ,2 ]
Liu F. [1 ,2 ]
机构：
[1] School of Computer Science and Technology, Xidian University, Xi'an
[2] Key Laboratory of Intelligent Perception and Image Understanding of the Ministry of Education of China, Xidian University, Xi'an
来源：
Liu, Fang (f63liu@163.com) | 1600年 / Science Press卷 / 39期
基金：
中国国家自然科学基金;
关键词：
Fuzzy membership; Image processing; Image semantic; Object detection; Very High Resolution SAR (VHR SAR);
D O I：
10.11999/JEIT160650
中图分类号：
学科分类号：
摘要：
It is hard to select a probability distribution model for very high resolution SAR images. This paper presents a novel method for the automatic detecting of cars from VHR SAR image without the probability distribution model. The proposed method starts with searching bright regions and dark regions by the gray feature. Subsequently, the fuzzy membership is employed to extract the semantic features of car from bright regions and dark regions. The potential scattering surface and shadow are matched and calculated with the spatial semantic relationship. Finally, the cars are selected from the matching. The efficiency of the proposed method is demonstrated by experiment which shows it still has high detection rate without the probability distribution model. © 2017, Science Press. All right reserved.
引用
收藏
页码：968 / 972
页数：4
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