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Automatic detection of knives in infrared images

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Citations (Scopus)

Abstract

The researchers present an experiment on automatic detection of concealed knives in infrared (IR) images. The researchers generated a dataset, called the IR dataset, which contained 8,527 images. The dataset was divided into two groups of IR images comprised of person without knife and person with a knife. Knives of different shapes and sizes were concealed under normal clothing, then images of person subjects carrying hidden knives were taken with a smartphone IR camera add-on. A deep neural network that was trained on natural image (GoogleNet dataset) was fine-tuned to classify the IR images as person, or person carrying hidden knife. The classification accuracy on a separate test set shows that hidden knives can be detected at 97.91% accuracy.

Original languageEnglish
Title of host publication1st International ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering, ECTI-NCON 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages65-68
Number of pages4
ISBN (Electronic)9781509052097
DOIs
Publication statusPublished - 8 Jun 2018
Event1st International ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering, ECTI-NCON 2018 - Chiang Rai, Thailand
Duration: 25 Feb 2018 → 28 Feb 2018

Publication series

Name1st International ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering, ECTI-NCON 2018

Conference

Conference1st International ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering, ECTI-NCON 2018
Country/TerritoryThailand
CityChiang Rai
Period25/02/18 → 28/02/18

Keywords

  • IR camera
  • Infrared images
  • Knife
  • Person
  • Smartphone

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