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Vehicle extraction from high-resolution satellite image using Template matching

机译:使用模板匹配从高分辨率卫星图像中提取车辆

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The process of vehicle examination by using satellite images is complicated and cumbersome process. At the present, the high definition satellite images are being used, however, the images of the vehicles can be seen as just a small point which is difficult to separate it out from the background that the image details are not sufficient to identify small objects. In this research, the techniques for the process of vehicle examination by using satellite images were applied by using image data from Pleiades which is the satellite image with high resolution of 0.40 m. The objective of this research is to study and develop the device for data extracting from satellite images, and the received data would be organized and created as Geospatial information by the concept of the picture matching with a pattern matching or Template Matching developed with Matlab program and Sum of Absolute Difference method collaborated with Neural Network technique in order to help evaluating pattern matching between template images of cars and cars' images which were used to examine from satellite images. The result obtained from the comparison with template data shows that data extraction accuracy is greater than 90%, and the extracted data can be imported into Geospatial information database. Moreover, the data can be displayed in Geospatial information Software, and it also can be searched by quantity condition and satellite image position.
机译:使用卫星图像的车辆检查过程是复杂的和繁琐的过程。目前,正在使用高清晰度卫星图像,然而,车辆的图像可以被视为仅难以将其从图像细节不足以识别小对象的背景的小点。在该研究中,通过使用来自Pleiades的图像数据来应用通过使用卫星图像的卫星图像的车辆检查过程的技术,该卫星图像具有高分辨率为0.40米的卫星图像。本研究的目的是研究和开发用于从卫星图像提取的数据提取的设备,并且通过与MATLAB程序开发的模式匹配或模板匹配的图像匹配的概念来组织和创建接收的数据作为地理空间信息。用神经网络技术合作的绝对差分方法的总和,以帮助评估用于从卫星图像检查的汽车和汽车的模板图像模板图像之间的模式匹配。与模板数据的比较获得的结果表明,数据提取精度大于90%,并且可以将提取的数据导入地理空间信息数据库。此外,数据可以在地理空间信息软件中显示,并且还可以由数量条件和卫星图像位置搜索。

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