计算机科学 ›› 2021, Vol. 48 ›› Issue (6A): 255-259.doi: 10.11896/jsjkx.200900033
陈扬1,2, 王金亮3, 夏炜3, 杨颢1,2, 朱润3, 奚雪峰1,2
CHEN Yang1,2, WANG Jin-liang3, XIA Wei3, YANG Hao1,2, ZHU Run3, XI Xue-feng1,2
摘要: 足迹图像是公安在串并案的侦破过程中最为重要的线索,且每年各处公安都会收集很多犯罪现场的足迹,如何自动化地整理和归类这些足迹图像成为当前公安信息化的一个难点。面向公安实战需求,文中结合卷积神经网络和DBSCAN算法,提出了一种对足迹图像聚类的方法。首先,对足迹图像进行预处理以便满足模型训练要求;接着,通过模型预训练改进了Resnnet50和Densenet121两类卷积神经网络模型结构,提取足迹图像特征并建立特征向量库;随后,基于DBSCAN聚类算法,利用上述特征向量库实现对足迹图像的整理归类。实验结果表明,该方法具有良好的实用性和有效性。
中图分类号:
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