Image Recognition Method of Multi-channel Convolutional Neural Network

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Image Recognition Method of Multi-channel Convolutional Neural Network

Journal Title: 河南科技大学学报（自然科学版） - Year 2017, Vol 38, Issue 3

Abstract

To make better use of the feature information implied in the image database,a multi-channel convolutional neural network image recognition method based on image gradients was proposed by making the multi-directional gradients information as basic expression of edge information. Firstly,four gradient images of horizontal,vertical,and two diagonal directions were obtained by processing the image through Sobel operation.Then,four multi-channel convolutional neural network was built to learn the features of gradient images of four different directions,and the features of four different directions were fused by stochastic feature fusion. Finally,the classification results were obtained through the classifier after batch normalization process for the features of samples. The proposed model was verified on database Cifar-10 and MNIST. The results show that the proposed model has better generalization ability,and its recognition error rates are reduced by 9. 85% and 0. 38%respectively compared to single-channel convolution neural network in the two databases.

Authors and Affiliations

Chaoren YI, Yanni DENG

Keywords

convolutional neural network; multi-channel; gradient image; stochastic feature fusion; classification;

EP ID EP478054
DOI -
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