Corpus ID: 16104553

Concealed Weapon Detection in a Human Body by Infrared Imaging

  title={Concealed Weapon Detection in a Human Body by Infrared Imaging},
  author={Mahadevi Parande and Shridevi Soma},
The detection of weapon concealed underneath a person’s cloths is very much important for the security of the public as well as the safety of public assets like airports, buildings, and railway stations etc. The goal is to develop an automatic detection and recognition system of concealed weapons using sensor technologies and image processing. The goal of this paper is to present the Concealed Weapon Detection method by infrared imaging (IR). Normal image is the human perception vision, whereas… Expand
Detection Of Concealed Weapons Using Image Processing Techniques: A Review
  • R. Mahajan, Devanand Padha
  • Computer Science
  • 2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC)
  • 2018
The researchers have focused on techniques to track and detect concealed objects, which involves the feature extraction of arms, segmentation of images with any concealed object and detection of the weapon. Expand
An alternative method to discover concealed weapon detection using critical fusion image of color image and infrared image
  • Nashwan Jasim Hussein, Fei Hu
  • Computer Science
  • 2016 First IEEE International Conference on Computer Communication and the Internet (ICCCI)
  • 2016
This paper introduced the detailed procedure, algorithms and systematic framework of automatic weapon detection approach for robust detection weapons hidden in clothes by using color image and infrared image as input and then applying process of image fusion with discrete wavelet transform analysis and segmentation using thresholding method. Expand
ADoCW: An Automated method for Detection of Concealed Weapon
A novel framework for the detection and classification of concealed weapons through analysis of CCTV stream data is proposed and faster R-CNN (Region-based Convolutional Neural Network) model is trained for classification of weapons over collected dataset. Expand
Anti-3D Weapon Model Detection for Safe 3D Printing Based on Convolutional Neural Networks and D2 Shape Distribution
The purpose of the proposed algorithm is to detect anti-3D weapon models when they are used in 3D printing based on the D2 shape distribution and an improved convolutional neural networks (CNNs). Expand


The detection of weapons concealed underneath a person’s clothing is an important obstacle to the improvement of the security of the general public as well as the safety of public assets likeExpand
Scanning baggage by x-ray and analysing such images have become important technique for detecting illicit materials in the baggage at Airports. In order to provide adequate security, a reliable andExpand
Portable concealed weapon detection using millimeter-wave FMCW radar imaging
Unobtrusive detection of concealed weapons on persons or in abandoned bags would provide law enforcement a powerful tool to focus resources and increase traffic throughput in high- risk situations.Expand
Fusion of Infrared and Visible Images for Robust Person Detection
To automate the system, a robust person detection algorithm and the development of an efficient technique enabling the fusion of the information provided by the two sensors becomes necessary and these are described in this chapter. Expand
Multiscale Fusion of Visible and Thermal IR Images for Illumination-Invariant Face Recognition
AbstractThis paper describes a new software-based registration and fusion of visible and thermal infrared (IR) image data for face recognition in challenging operating environments that involveExpand
Contour Detection of Human Knee *
Medical images (X-ray, CT, MR or PET) of human organs are widely used in the everyday clinical praxis. The paper presents methods which allows the user to analyze, model and adjust the total kneeExpand
Pixel Level Image Fusion using FuzzyletFusion Algorithm
It was observed that fusion using SWT with higher levels of decomposition provides better fusion results and Fuzzy image fusion with more number of membership functions provides better results. Expand
Pixel Level Image Fusion using Fuzzy let Fusion Algorithm " , an ISO 3297: 2007 Certified Organization
  • Pixel Level Image Fusion using Fuzzy let Fusion Algorithm " , an ISO 3297: 2007 Certified Organization
  • 2013
Pixel Level Image Fusion using Fuzzy let Fusion Algorithm”, an ISO
  • Certified Organization,
  • 2007
Kong,”Multiscale Fusion of Visible and Thermal IR Images for Illumination-Invariant Face Recognition”, the University of Tennessee, and Knoxville, TN 37996-2100
  • First online version published in June,
  • 2006