TY - GEN
T1 - Towards automatic inspection
T2 - 2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018
AU - Vazquez-Nicolas, J. M.
AU - Zamora, Erik
AU - Gonzalez-Hernandez, I.
AU - Lozano, Rogelio
AU - Sossa, Humberto
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/31
Y1 - 2018/8/31
N2 - Building inspection searching for superficial defects, such as cracks, is a vital task because such damages cause economic losses or put at risk the integrity of people. For this reason, different ways to reduce the costs and risks through the use of robotic systems that allow make inspections have been studied. Among these robotic systems, we have the unmanned aerial vehicles (UAV) that allow reaching difficult access places permitting better inspection. In this work, we propose using convolutional neuronal networks for crack recognition from images captured by an UAV. To carry out the training task of the network, a database of cracks in walls was built from images collected from the Internet. The training of the network prompted encouraging results with a 95% accuracy over the training set. Experimental results of crack recognition in images were carried out validating the application of the proposal.
AB - Building inspection searching for superficial defects, such as cracks, is a vital task because such damages cause economic losses or put at risk the integrity of people. For this reason, different ways to reduce the costs and risks through the use of robotic systems that allow make inspections have been studied. Among these robotic systems, we have the unmanned aerial vehicles (UAV) that allow reaching difficult access places permitting better inspection. In this work, we propose using convolutional neuronal networks for crack recognition from images captured by an UAV. To carry out the training task of the network, a database of cracks in walls was built from images collected from the Internet. The training of the network prompted encouraging results with a 95% accuracy over the training set. Experimental results of crack recognition in images were carried out validating the application of the proposal.
UR - http://www.scopus.com/inward/record.url?scp=85053880060&partnerID=8YFLogxK
U2 - 10.1109/ICUAS.2018.8453390
DO - 10.1109/ICUAS.2018.8453390
M3 - Contribución a la conferencia
AN - SCOPUS:85053880060
SN - 9781538613535
T3 - 2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018
SP - 654
EP - 659
BT - 2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 12 June 2018 through 15 June 2018
ER -