Enhancements in image quality and block detection performance for Reinforced Soil-Retaining Walls under various illuminance conditions SCIE SCOPUS

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Title
Enhancements in image quality and block detection performance for Reinforced Soil-Retaining Walls under various illuminance conditions
Author(s)
Ha, Yong-Soo; Oh, Myoung Hak; Pham, Minh-Vuong; Lee, Ji-Sung; Kim, Yun-Tae
KIOST Author(s)
Ha, Yong-Soo(하용수)Oh, Myoung Hak(오명학)
Alternative Author(s)
하용수; 오명학
Publication Year
2024-09
Abstract
To ensure continuous monitoring of reinforced soil-retaining walls (RSWs) even under low-illuminance condi- tions, such as during the night, it is imperative to evaluate the performance of deep learning-based detection. In this study, we constructed a laboratory RSW model and generated a dataset with varying illuminance levels to assess the impact of image enhancement and block detection. Various image enhancement methods were applied to improve image quality and evaluate their effect on deep learning. RGB optimization (RO) was proposed to optimize RGB intensity and compared with gamma correction, histogram equalization, and low-light image enhancement with illumination map estimation. RO demonstrated outstanding image enhancement perfor- mance, as evidenced by lightness order error, peak signal-to-noise ratio, and structural similarity index measure, ensuring high image quality. The trained RO model using Mask R-CNN exhibited excellent accuracy, recall, and F1 score, delivering remarkable detection performance under low illuminance conditions, resulting in a 7.44 % improvement in the F1 score. Image enhancement techniques that maintain similarity, such as lightness order error and structural similarity, across varying illuminance conditions contribute to enhancing the block detection performance of Mask R-CNNs.
ISSN
0965-9978
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/45744
DOI
10.1016/j.advengsoft.2024.103713
Bibliographic Citation
Advances in Engineering Software, v.195, 2024
Publisher
Pergamon Press Ltd.
Keywords
Reinforced soil-retaining walls; Illuminances; Image enhancement; RGB optimization; Mask R-CNN
Type
Article
Language
English
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