Agung Teguh Wibowo Almais, Adi Susilo, Agus Naba, Moechammad Sarosa, Alamsyah Muhammad Juwono, Cahyo Crysdian, Muhammad Aziz Muslim, Hendro Wicaksono
Objective: To determine the characteristics of a building after a natural disaster using image input through the integration of image analysis techniques. Methods: Several image analysis techniques, including GLCM and PCA, were employed. The GLCM process converts image input into numerical values using 8 different angles and pixel distances of 1 and 0.5 pixels. The numerical values from GLCM are then processed by PCA to extract information stored in the images of buildings post-disaster. Results: The PCA process revealed different information between images processed with GLCM at 1 pixel distance and those at 0.5 pixel distance. Validation by surveyors confirmed that the accurate information corresponding to real images was obtained from GLCM with a 0.5 pixel distance, indicating severe damage. The PCA results using GLCM at 0.5 pixel distance produced 2D and 3D visualizations with dominant coordinates in the severely damaged cluster, with a value range (n) of n ≥ 2. Conclusion: Based on these findings, the integration of image analysis techniques, specifically GLCM and PCA, can be used to determine the level of damage to buildings after a natural disaster. © 2024 The Authors.
Department of Physics, Universitas Brawijaya, Malang, 65145, Indonesia; Department of Informatics Engineering, Universitas Islam Negeri Maulana Malik Ibrahim Malang, Malang, 65144, Indonesia; Electrical Engineering, State Polytechnic of Malang, Malang, 65141, Indonesia; Department of Electrical Engineering, Universitas Brawijaya, Malang, 65145, Indonesia; School of Business, Social, and Decision Science, Constructor University, Bremen, 28759, Germany
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