摘要
X光安检图像违禁品分类被广泛应用于协助维护航空和运输安全。针对X光安检图像中违禁品尺度不一、存在困难样本及旅客行李安检固有的正负样本不均衡等问题,提出一种端到端的考虑样本不平衡的X光安检图像违禁品分类方法。采用多尺度特征提取网络捕获尺度不一的多类型违禁品特征,通过特征融合模块提升模型对图像边缘和纹理特征的表达能力,基于代价敏感思想设计损失函数,解决数据集不平衡问题,并提高困难样本分类精准度。在公开数据集SIXray上构建的子集实验结果表明:所提方法相较于端到端分类模型,平均AP指标值提升了4.5%,特别是对剪刀等难分类样本,AP指标值都有显著的提升效果。
X-ray security image contraband classification is widely used to assist in maintaining aviation and transportation security.This paper suggests an end-to-end X-ray security inspection image classification method that takes sample imbalance into account in order to address the issues of different scales of contraband in X-ray images,challenging samples,and unbalanced positive and negative samples inherent in passenger baggage security inspection.The feature fusion module is used to enhance the model’s ability to express picture edge and texture features while the multi-scale feature extraction network is used to capture the features of numerous sorts of illegal goods with various scales.Based on the cost-sensitive idea,the loss function is designed to solve the problem of dataset imbalance,and improve the classification accuracy of difficult samples.The experimental results of the subset constructed on the public dataset SIXray show that the proposed method improves the mean AP index by 4.5%compared with the current optimal end-to-end classification model,especially for hard-to-classify samples such as scissors,the AP index has a significant improvement effect.
作者
冯霞
魏新坤
刘才华
赫鑫宇
FENG Xia;WEI Xinkun;LIU Caihua;HE Xinyu(School of Computer Science and Technology,Civil Aviation University of China,Tianjin 300300,China;Key Laboratory of Intelligent Airport Theory and System,CAAC,Tianjin 300300,China)
出处
《北京航空航天大学学报》
EI
CAS
CSCD
北大核心
2023年第12期3215-3221,共7页
Journal of Beijing University of Aeronautics and Astronautics
基金
天津市教委科研计划(2021KJ037)
中央高校基本科研业务费专项资金(3122021052)。
关键词
违禁品分类
样本不平衡
X光图像
多尺度
困难样本分类
代价敏感
contraband classification
sample imbalance
X-ray images
multi-scale
difficult sample classifi-cation
cost-sensitive
