Pulse-coupled neural network based on an adaptive Gabor filter for pavement crack segmentation
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Abstract
This article proposes a Pulse-Coupled Neural Network based on an adaptive Gabor filter for the segmentation of cracks in the pavement in digital images. By estimating the noise in the image, the parameters of the filter that convolves the neurons of the model are adjusted. As a result iterations were reduced to 2%
with ? 90% precision. The algorithm was parallelized on the GPU and the processing time was reduced to n/NM regardless of the M and N dimensions of the
image.
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Luna Álvarez, A., Mújica Vargas, D., Rubio, J. de J., & Rosales Silva, A. (2024). Pulse-coupled neural network based on an adaptive Gabor filter for pavement crack segmentation. Journal of Applied Research and Technology, 22(1), 102–110. https://doi.org/10.22201/icat.24486736e.2024.22.1.1837
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