Method for Indoor Seismic Intensity Assessment Based on Image Processing Techniques

The seismic intensity experienced indoors directly reflects the degree of damage to the internal structure of the building. The current classification of indoor strength relies on manual surveys and qualitative descriptions of macro phenomena, which are subjective, unable to capture real-time dynamic changes in the room, and lack quantitative indicators. In this paper, we present the Image Evaluation of Seismic Intensity (IESI) method, which is based on image processing technology. This method mainly evaluates the degree of responses from objects by identifying the percentage of movement of different types of objects in images taken before and after an earthquake. In order to further improve the recognition accuracy, we combined the camera vibration degree and the object displacement between images to correct the generated earthquake intensity level estimation, so as to achieve the rapid assessment of an earthquake's intensity indoors. We took, as an example, 29 sets of seismic data from different scenarios. We used the IESI method to evaluate the seismic intensity of these scenarios. Compared with the seismic intensity evaluation results obtained by the Post-disaster Sensor-based Condition Assessment of Buildings (PSAB) and the Image-based Seismic Damage Assessment System (IDEAS) methods, the accuracy of the IESI method was higher by more than 30%, and its accuracy reached 97%. The universality of the IESI method in different indoor scenarios was demonstrated. In a low-intensity evaluation experiment, the accuracy of the IESI method also reached 91%, which verifies the reliability of the IESI method in low-intensity regions.

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Publication Details

Journal
Journal of Imaging
Published
2025-04-22
DOI
https://doi.org/10.3390/jimaging11050129
Citations
1
Primary Topic
Infrastructure Maintenance and Monitoring
Type
article
Field-Weighted Citation Impact
0.95
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article

Method for Indoor Seismic Intensity Assessment Based on Image Processing Techniques

Jingsong Yang, Guoxing Lu, Yanxiong Wu, Fengguang Peng
1 citations
Journal of Imaging
Infrastructure Maintenance and Monitoring
0.95
article

Method for Indoor Seismic Intensity Assessment Based on Image Processing Techniques

Jingsong Yang, Guoxing Lu, Yanxiong Wu, Fengguang Peng
article en
1 citations

Abstract

The seismic intensity experienced indoors directly reflects the degree of damage to the internal structure of the building. The current classification of indoor strength relies on manual surveys and qualitative descriptions of macro phenomena, which are subjective, unable to capture real-time dynamic changes in the room, and lack quantitative indicators. In this paper, we present the Image Evaluation of Seismic Intensity (IESI) method, which is based on image processing technology. This method mainly evaluates the degree of responses from objects by identifying the percentage of movement of different types of objects in images taken before and after an earthquake. In order to further improve the recognition accuracy, we combined the camera vibration degree and the object displacement between images to correct the generated earthquake intensity level estimation, so as to achieve the rapid assessment of an earthquake's intensity indoors. We took, as an example, 29 sets of seismic data from different scenarios. We used the IESI method to evaluate the seismic intensity of these scenarios. Compared with the seismic intensity evaluation results obtained by the Post-disaster Sensor-based Condition Assessment of Buildings (PSAB) and the Image-based Seismic Damage Assessment System (IDEAS) methods, the accuracy of the IESI method was higher by more than 30%, and its accuracy reached 97%. The universality of the IESI method in different indoor scenarios was demonstrated. In a low-intensity evaluation experiment, the accuracy of the IESI method also reached 91%, which verifies the reliability of the IESI method in low-intensity regions.

Journal of ImagingVol. 11(5)
Institute of Disaster Prevention (CN)
Climate action
Openalex Percentile: Top 27%
Infrastructure Maintenance and Monitoring
0.95
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Method for Indoor Seismic Intensity Assessment Based on Image Processing Techniques — Jingsong Yang, Guoxing Lu, et al. · Journal of Imaging (2025) | TGRS Research Map | TGRS