Multispectral imaging for improved liquid classification in security sensor systems

Andrea Burns, Waheed Uz Zaman Bajwa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Multispectral imaging can be used as a multimodal source to increase prediction accuracy of many machine learning algorithms by introducing additional spectral bands in data samples. This paper introduces a newly curated Multispectral Liquid 12-band (MeL12) dataset, consisting of 12 classes: eleven liquids and an empty container class. Multispectral images in this dataset have been captured using the PCO Ultraviolet, Grasshopper3 12.3 MP Color USB3 Vision, Mil-Rugged-High Resolution Snapshot Short Wave Infrared 1280JS, FLIR Medium Wave Infrared A6750sc and FLIR Long Wave Infrared T650sc cameras. Each of the classes initially results in a 640 × 480 × 12 data cube, where the 12 × 1 vector for each spectral pixel spans the spectral bands observed using the above-mentioned cameras and seven add-on bandpass optical filters. The usefulness of multispectral imaging in classification of liquids is demonstrated through the use of a support vector machine on MeL12 for classification of the 12 classes. The reported results are both encouraging and point to the need for additional work to improve liquid classification of harmless and dangerous liquids in high-risk environments, such as airports, concert halls, and political arenas, using multispectral imaging.

Original languageEnglish (US)
Title of host publicationAlgorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV
EditorsDavid W. Messinger, Miguel Velez-Reyes
PublisherSPIE
ISBN (Electronic)9781510617995
DOIs
StatePublished - Jan 1 2018
EventAlgorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV 2018 - Orlando, United States
Duration: Apr 17 2018Apr 19 2018

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10644
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Other

OtherAlgorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV 2018
Country/TerritoryUnited States
CityOrlando
Period4/17/184/19/18

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Keywords

  • Liquid classification
  • Machine learning
  • Multispectral imaging
  • Support vector machine

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