Publication: Automatic detection of knives in infrared images
Issued Date
2018-06-08
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2-s2.0-85049945756
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Mahidol University
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SCOPUS
Bibliographic Citation
1st International ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering, ECTI-NCON 2018. (2018), 65-68
Suggested Citation
Sumeth Yuenyong, Narit Hnoohom, Konlakorn Wongpatikaseree Automatic detection of knives in infrared images. 1st International ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering, ECTI-NCON 2018. (2018), 65-68. doi:10.1109/ECTI-NCON.2018.8378283 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/45626
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Title
Automatic detection of knives in infrared images
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Abstract
© 2018 IEEE. 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.