Pulse-coupled neural network based on an adaptive Gabor filter for pavement crack segmentation

Main Article Content

A. Luna Álvarez
D. Mújica Vargas
https://orcid.org/0000-0001-8665-4096
J. de J. Rubio
A. Rosales Silva

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.

Article Details

How to Cite
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
Section
Articles
Author Biography

A. Luna Álvarez, Computer Science Department, Tecnológico Nacional de México/CENIDET, Cuernavaca, Morelos, México



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