现勘图像检索综述

doi:10.3969/j.issn.0372-2112.2018.03.035

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摘要现勘图像检索是进行证据图像比对以获取物证信息的重要手段.本文基于目前应用广泛的现勘图像数据库，根据图像内容将图像分为鞋印、指纹、纹身等种类.并通过对现勘图像的两项关键技术即低层数字特征提取和高层语义分析的总结，从颜色特征、纹理特征、边缘提取等方面综述了现勘图像低层数字特征提取技术，从利用语义模板和数据库本体结构、机器学习算法、引入人工反馈三大类高层语义提取技术综述了现勘图像高层语义分析的研究成果.最后，结合公安行业利用现勘图像获取物证线索的实际应用需求，指出了通过引入公安行业先验知识来提高检索效率等研究方向.

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	刘颖
	胡丹
	范九伦

关键词 ：现勘图像检索, 现勘图像数据库, 低层数字特征, 高层语义特征

Abstract：Crime scene investigation (CSI) image retrieval is an important means to obtain material evidence for case solving.This paper describes the CSI image datasets,which are classified into different categories according to the content of the data,such as shoe marks,finger prints,tattoo,etc.This paper provides a survey on state-of-the-art techniques in CSI image retrieval focusing on low-level feature extraction and high-level semantic learning.Low-level CSI image features mainly include color feature,texture feature,boundary descriptor,etc.And,three categories of high-level semantic extraction techniques for CSI images are identified including using semantic template and database ontology,machine learning techniques and introducing relevance feedback.In addition,based on practical requirements from the police on using CSI images to find evidence clues,a few research directions are suggested such as introducing prior knowledge of the police to enhance retrieval efficiency.

Key words： crime scene investigation image retrieval crime scene investigation image database low-level digital feature extraction high-level semantic learning

收稿日期: 2016-12-02 出版日期: 2017-03-27

ZTFLH:

TP391.41

基金资助:公安部科技强警（No.2016GABJC51）；国家自然科学基金（No.61671377）

作者简介: 刘颖,女,1972年1月生于陕西省户县,教授、硕士生导师.2007年获得澳大利亚莫纳什大学博士学位.现为西安邮电大学通信与信息工程学院副院长、电子信息现场勘验应用技术公安部重点实验室总工程师,主要研究方向为图像分析与检索.E-mail:ly_yolanda@sina.com;胡丹,女,1990年10月生于河南省原阳县.2015年进入西安邮电大学通信与信息工程学院学习,硕士研究方向为图像检索.E-mail:hudandan803@163.com;范九伦,男,1964年11月生于河南省温县,教授,博士生导师.1998年获西安电子科技大学博士学位,现为西安邮电大学校长,主要研究方向为模糊信息处理、图像处理、信息安全等.E-mail:jiulunf@xupt.edu.cn

引用本文:

刘颖, 胡丹, 范九伦. 现勘图像检索综述[J]. 电子学报, 2018, 46(3): 761-768. LIU Ying, HU Dan, FAN Jiu-lun. A Survey of Crime Scene Investigation Image Retrieval. Acta Electronica Sinica, 2018, 46(3): 761-768.

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http://www.ejournal.org.cn/CN/10.3969/j.issn.0372-2112.2018.03.035 或 http://www.ejournal.org.cn/CN/Y2018/V46/I3/761

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