Video keyframe extraction algorithm for highway tunnel cracks based on the combination of MSF and FCD
To address the issues of low accuracy and slow speed in extracting keyframes from highway tunnel videos,this study proposes an efficient extraction algorithm for crack keyframe extraction,inte-grating Multi-Scale Filtering(MSF)and Ridge Change Detection(RCD).First,a crack ridge feature extraction method is developed based on multi-scale filtering and the Hessian matrix,considering the gradient and second-order derivative properties of cracks across various directions and scales.Using ei-genvalue computation and threshold analysis,ridge lines from different scale filtering results are ex-tracted and fused,enabling precise extraction of crack ridge features in highway tunnel videos.Then,an indexing spatial model for road crack video frames is proposed.By employing ridge differential analysis and inter-frame dissimilarity constraints,a crack keyframe indexing mechanism is con-structed.Dynamic characteristics of crack regions are identified through ridge change detection,while representative keyframes are selected using inter-frame dissimilarity discrimination.This approach re-duces redundant frames and significantly improves the efficiency of video processing for crack detec-tion.Finally,experiments are conducted to extract keyframes from highway tunnel crack videos.The experimental results demonstrate that the proposed method improves accuracy by 19.3%to 43.2%compared to existing keyframe extraction methods,with average keyframe extraction speeds being 11 to 13 times faster than motion-based methods.This method effectively enhances highway tunnel crack detection efficiency and provides valuable insights for intelligent crack detection in highway tunnels.
万方数据
维普
