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Crack detection algorithm

Open and Stream video with Python and OpenCV. Detect Objects, including corner, edge, and grid detection techniques with OpenCV and Python . Jan 28, 2021 · (Image by Author) From this image, we might choose a thresholding value of 0.40.

Actually, cracks usually appear as thin black bands with different angles and directions. Region proposal-based target detection algorithms can detect cracks well, but cannot provide accurate information about the direction and size of cracks..

Pavement crack is one of the main factors threatening highway safety. Rapid and accurate identification of pavement crack is very important to protect highway. Traditional image processing methods have been difficult to meet the requirements of practical engineering. So, this paper proposes an improved pavement crack detection method based on deep convolution neural network model, to overcome.

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Cracks in oil paintings constitute an undesirable but unavoidable effect of time, deteriorating the painting quality. This work proposes a crack detection method that supports the physical restoration process of the artworks, providing a fissure map that allows the artist to visualize the pictorial layer and its flaws.

Therefore, this paper proposes a dynamic partitioned Gaussian crack detection algorithm based on the projection curve distribution. First, according to the distribution of the image projection curve, the background pixels are dynamically partitioned. Second, a new dynamic partitioned Gaussian (DPG) model was established, and the set rules of.

Jul 17, 2020 · From two aspects of qualitative and quantitative analysis, the experimental results demonstrate that this algorithm could effectively eliminate the effect of uneven illumination on crack detection. After detection, Recall could reach more than 96%, and after extraction, Precision was increased by more than 70%..

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