Extracting crack in mining areas based on dynamic snake-dilation convolution model

doi:10.13474/j.cnki.11-2246.2024.1024.

Abstract

Abstract: Mining cracks are a common type of damage that occurs in coal mines due to underground mining. Aiming at the problems of complex surface environment in mining areas and low accuracy of crack extraction methods in UAV images, this studyfused the dynamic snake convolution and dilation convolution to construct a new dynamic snake-dilation convolution. The proposed convolution is added to the encoding and decoding structure of the reference model to optimize the overall network structure; In addition, constructed a crack dataset of the mining area, and verified the accuracy of the crack extraction on this custom dataset. The results show that the addition of dynamic snake-dilation convolution can improve the segmentation accuracy (mean intersection over union) of the model by 14.96%, which is of practical value for achieving accurate extraction of ground cracks.

Key words: underground mining, ground surface crack, unmanned aerial vehicle, crack extraction, dynamic snake-dilation convolution, precision assessment

CLC Number:

WANG Xiaoyu, CAI Yinfei, HU Haifeng. Extracting crack in mining areas based on dynamic snake-dilation convolution model[J]. Bulletin of Surveying and Mapping, 2024, 0(10): 144-150.

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