MIAO S, LI X W, YANG Y,et al.Detection of contraband in X-ray images based on improved Capsule network[J].Journal of Henan Polytechnic University(Natural Science) ,2023,42(3):129-136.

doi:10.16186/j.cnki.1673-9787.2021080065

Received:2021/08/18

Revised:2021/11/24

Published:2023/05/25

Detection of contraband in X-ray images based on improved Capsule network

MIAO Shuo1, LI Xinwei1, YANG Yi1, WANG Keping1, CUI Kefei2

1.Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment，Henan Polytechnic University，Jiaozuo  454000，Henan，China;2.Zhengmeiji Hydraulic Electric Control Co.，Ltd.，Zhengzhou  450016，Henan，China

Abstract:Aiming at the problems of missing and false detection in X-ray image contraband detection，a model based on improved Capsule network（DSCapsule）was proposed.Feature enhancement block（DMF）and feature screening block（SE）were added in this model.Firstly，feature enhancement block was used to extract image features，and feature information was obtained by adding dilated convolution layers and splicing the semantic features of high and low layers.Secondly，the feature screening block was used to screen the obtained features by Squeezing and Excitation.Finally，the detection of contraband was completed through the Capsule layer of the network.In order to verify the detection ability of the model for contraband in complex X-ray images，the model was verified on SIXray dataset.The accuracy of the model reached 79.254%，which was 7.904% higher than the original Capsule network（71.350%）.Therefore，the detection ability of the improved model was significantly improved.

Key words:contraband detection;Capsule network;dilated convolution;multi-feature fusion;feature selection

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