Article: Extraction of crack characteristics and local damage detection in complex hydraulic concrete structures Journal: International Journal of Critical Infrastructures (IJCIS) 2026 Vol.22 No.8 pp.1 - 15 Abstract: Crack detection in complex hydraulic structures is often challenged by background interference, which obscures crack contours and hampers accurate damage localisation. This paper proposes a novel method to address this issue. First, an image compression technique integrating YCbCr conversion, visually weighted wavelet transform, and embedded zero-tree coding is introduced to enhance crack saliency and reduce redundancy. Subsequently, crack edges are continuously and precisely extracted using an adaptive dual-threshold Canny operator. Finally, pixel-level damage detection is achieved with an encoder-decoder model based on SegNet, trained via the Nadam optimiser. Experimental results demonstrate the superiority of our approach, achieving a detection accuracy of 96.2%, a mean intersection over union of 95.6%, and an F1-score of 0.97, significantly outperforming existing methods. The proposed technique provides a reliable and robust solution for the intelligent diagnosis of hydraulic engineering structures. Inderscience Publishers - linking academia, business and industry through research

Title: Extraction of crack characteristics and local damage detection in complex hydraulic concrete structures

Authors: Ye He; Bijian Zhou; Ying Cai; Yibin Zhang

Addresses: School of Civil Engineering, Hunan City University, Yiyang, 413000, China ' Yiyang City Urban Construction Investment and Operation Group Co., Ltd., Yiyang, 413000, China ' School of Civil Engineering, Hunan City University, Yiyang, 413000, China ' School of Civil Engineering, Hunan City University, Yiyang, 413000, China

Abstract: Crack detection in complex hydraulic structures is often challenged by background interference, which obscures crack contours and hampers accurate damage localisation. This paper proposes a novel method to address this issue. First, an image compression technique integrating YCbCr conversion, visually weighted wavelet transform, and embedded zero-tree coding is introduced to enhance crack saliency and reduce redundancy. Subsequently, crack edges are continuously and precisely extracted using an adaptive dual-threshold Canny operator. Finally, pixel-level damage detection is achieved with an encoder-decoder model based on SegNet, trained via the Nadam optimiser. Experimental results demonstrate the superiority of our approach, achieving a detection accuracy of 96.2%, a mean intersection over union of 95.6%, and an F1-score of 0.97, significantly outperforming existing methods. The proposed technique provides a reliable and robust solution for the intelligent diagnosis of hydraulic engineering structures.

Keywords: hydraulic construction; concrete structure; crack characteristics; damage detection.

DOI: 10.1504/IJCIS.2026.152010

International Journal of Critical Infrastructures, 2026 Vol.22 No.8, pp.1 - 15

Received: 17 Oct 2025
Accepted: 15 Dec 2025
Published online: 02 Mar 2026 *

Title: Extraction of crack characteristics and local damage detection in complex hydraulic concrete structures

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