High-altitude parabolic identification technology for urban buildings

Xiao Zhao; Yuechen Li; Chen Yang; Ruonan Wang; Hui Zhang; Jingxia Chen

doi:10.1117/12.2635430

6 May 2022 High-altitude parabolic identification technology for urban buildings

Xiao Zhao, Yuechen Li, Chen Yang, Ruonan Wang, Hui Zhang, Jingxia Chen

Proceedings Volume 12256, International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2022); 122560H (2022) https://doi.org/10.1117/12.2635430
Event: 2022 International Conference on Electronic Information Engineering, Big Data and Computer Technology, 2022, Sanya, China

Abstract

A high-altitude parabolic identification technology for urban buildings is proposed, which aims at locating the parabolic position accurately and sending out warning signal in real-time to provide reference data for afterwards accountability. Firstly, the video image is preprocessed, and the color video image of the input is converted to the gray-scale video image. Secondly, the moving area is obtained by difference motion using three consecutive frames of images. Thirdly, the background subtraction model is used to obtain the complete moving object, and the complete moving object is obtained by performing OR operation with the former obtained moving object. Finally, the parabolic object is identified and the complete trajectory is obtained after further processing by using median filtering and morphological method. The parabolic coordinates correspond to the starting point is the corresponding floors. The algorithm not only can optimize the process of parabolic identification, but also remove the false identification of birds, leaves and other non-parabolic objects. The algorithm improve the accurate identification of multiple parabolic objects. The experimental results showed that the algorithm can correctly and effectively track the parabolic trajectory of urban buildings at high-altitude. It can locate the floors corresponding to the parabolic coordinates.

Citation Download Citation

Xiao Zhao, Yuechen Li, Chen Yang, Ruonan Wang, Hui Zhang, and Jingxia Chen "High-altitude parabolic identification technology for urban buildings", Proc. SPIE 12256, International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2022), 122560H (6 May 2022); https://doi.org/10.1117/12.2635430

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KEYWORDS

Video

Binary data

Image processing

Digital filtering

Image fusion

Detection and tracking algorithms

Image filtering

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