Computer Science ›› 2017, Vol. 44 ›› Issue (Z11): 207-211.doi: 10.11896/j.issn.1002-137X.2017.11A.043

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Automatic Recognition Method of Tunnel Disease Based on Convolutional Neural Network for Panoramic Images

TANG Yi-ping, HU Ke-gang and YUAN Gong-ping   

  • Online:2018-12-01 Published:2018-12-01

Abstract: In light of the current difficulty of getting panoramic image of the tunnel lining fast and conveniently,and the difficulty of detecting various diseases automatically,in this paper,we put forward a disease recognition method based on convolutional neural network (CNN) to address such problems.First,a panoramic visual sensor which can fast obtain the panoramic image of the whole tunnel section were designed,and then through digital image processing technology the panoramic images was dealt with including panoramic image unrolling,image processing and brinary processing to extract suspected disease regions.Finally,the diseases were classified automatically under convolutional neural network.The experiments demonstrate that the method can effectively simplify the structure of obtaining the panoramic image of the tunnel,achieve the automatic feature extraction detection and recognition through the end to end convolutional neural network,the rate of recognizing the diseases in panoramic image exceeds 88%,and this method provides effective technical support for tunnel maintenance and completion acceptance.

Key words: Tunnel,Panoramic image,Disease detection,Convolutional neural network

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