Computer Science ›› 2019, Vol. 46 ›› Issue (9): 265-270.doi: 10.11896/j.issn.1002-137X.2019.09.040

• Graphics,Image & Pattern Recognition • Previous Articles     Next Articles

Multi-spectral Scene Recognition Method Based on Multi-way Convolution Neural Network

JIANG Ze-tao1,2, QIN Jia-qi1, HU Shuo3   

  1. (The Key Laboratory of Image and Graphic Intelligent Processing of Higher Education in Guangxi,Guilin University of Electronic Technology,Guilin,Guangxi 541004,China)1;
    (The Key Laboratory of Dependable Software of Guangxi,Guilin University of Electronic Technology,Guilin,Guangxi 541004,China)2;
    (Nanchang Hangkong University,Nanchang 330063,China)3
  • Received:2018-08-03 Online:2019-09-15 Published:2019-09-02

Abstract: The existing scene recognition algorithm based on convolution neural network can’t deal with the multi spectral image of the target scene and can’t implement ideal accuracy in the case of insufficient data.In view of the above problems,this paper proposed a multi-spectral convolution neural network based multispectral scene recognition me-thod.The multi-way convolution neural network accepts three channels of visible light color image (RGB image) and a single channel near infrared image (NIR image) with a total of four channels.The proposed method can effectively extract the features of visible light image,infrared image and the correlation between visible and infrared images,and combine the features in the full connection layer,utilizing the correlation information among spectral images reasonably.The pre-training method is combined to improve the accuracy.Experiment results on the NIR_RGB dataset show that the average accuracy of the network is higher than that of AlexNet,InceptionNet,ResNet and artificial design feature descriptors.Moreover,this network can be extended to other multi-spectral image classification tasks with slight modification.

Key words: Convolution neural network, Image classification, Multi-spectral, Scene recognition

CLC Number: 

  • TP391.4
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