Design and Implementation of Trace Inspection System Based upon Hyperspectral Imaging Technology

Author:

Wang Yuchen12,Ji Zhongyuan13ORCID

Affiliation:

1. College of Criminal Justice, Shandong University of Political Science and Law, Jinan 250014, China

2. Key Laboratory of Evidence-Identifying in Universities of Shangdong, Shandong University of Political Science and Law, Jinan 250014, China

3. College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, Jiangsu, China

Abstract

Trace inspection is a key technology for collecting crime scenes in the criminal investigation department. A lot of information can be obtained by restoring and analyzing the remaining traces on the scene. However, with the development of digital technology, digital trace inspection has become more and more popular. So, the main research of this article is the design and realization of the trace inspection system based on hyperspectral imaging technology. This article proposes nondestructive testing technology in hyperspectral imaging technology. Combining basic principles of spectroscopy and the image of residual traces such as car tires, shoe soles, and blood stains, it can identify the key traces. Then, based on the image denoising and least squares support vector machine method, this study improves the accuracy and restoration of the image. Therefore, this study designs a test for the trace inspection system for testing hyperspectral imaging technology. The test items include the performance of the trace inspection system, the noise reduction of the trace inspection system, and the ability of the trace inspection system to inspect blood stains. The final collected data are improved to get the trace inspection system based on hyperspectral imaging technology proposed in this study. Compared with the traditional trace inspection system, the experimental results show that the trace inspection system based on hyperspectral imaging technology can improve the accuracy by 5%–28%, compared with the traditional trace inspection system. The image restoration degree of the hyperspectral imaging technology trace inspection system can be improved by 1%–19%, compared with the traditional trace inspection system.

Funder

Youth Innovation Team Development Project of Shandong Universities

Publisher

Hindawi Limited

Subject

General Mathematics,General Medicine,General Neuroscience,General Computer Science

Reference24 articles.

1. Salient band selection for hyperspectral image classification via manifold ranking;Q. Wang;IEEE Transactions on Neural Networks and Learning Systems,2017

2. Spectral–Spatial Classification of Hyperspectral Image Based on Deep Auto-Encoder

3. Hyperspectral Image Classification Via Shape-Adaptive Joint Sparse Representation

4. Hyperspectral image unmixing algorithm based on endmember-constrained nonnegative matrix factorization;Z. Yan;Frontiers of Optoelectronics,2016

5. Probabilistic class structure regularized sparse representation graph for semi-supervised hyperspectral image classification;Y. Shao;Pattern Recognition,2016

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3