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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Computer Science
Ammar Wisam Altaher
Al-Furat Al-Awsat Technical University
Computer Science & IT

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Image processing analysis of sigmoidal Hadamard wavelet with PCA to detect hidden object Ammar Wisam Altaher; Sabah Khudhair Abbas
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 3: June 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i3.13541

Abstract

Innovative tactics are employed by terrorists to conceal weapons and explosives to perpetrate violent attacks, accounting for the deaths of millions of lives every year and contributing to huge economic losses to the global society. Achieving a high threat detection rate during an inspection of crowds to recognize and detect threat elements from a secure distance is the motivation for the development of intelligent image data analysis from a machine learning perspective. A method proposed to reduce the image dimensions with support vector, linearity and orthogonal. The functionality of CWD is contingent upon the plenary characterization of fusion data from multiple image sensors. The proposed method combines multiple sensors by hybrid fusion of sigmoidal Hadamard wavelet transform and PCA basis functions. Weapon recognition and the detection system, using Image segmentation and K means support vector machine A classifier is an autonomous process for the recognition of threat weapons regardless of make, variety, shape, or position on the suspect’s body despite concealment.
Intelligent security system detects the hidden objects in the smart grid Ammar Wisam Altaher; Abdullah Hasan Hussein
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 1: July 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i1.pp188-195

Abstract

Monitoring the general public gathered in large numbers is one of the most challenging tasks faced by the law and order enforcement team. There is swiftly demand to that have inbuilt sensors which can detect the concealed weapon, from a standoff distance the system can locate the weapon with very high accuracy. Objects that are obscure and invisible from human vision can be seen vividly from enhanced artificial vision systems. Image Fusion is a computer vision technique that fuses images from multiple sensors to give accurate information. Image fusion using visual and infrared images has been employed for a safe, non-invasive standoff threat detection system. The fused imagery is further processed for specific identification of weapons. The unique approach to discover concealed weapon based on DWT in conjunction with Meta heuristic algorithm Harmony Search Algorithm and SVM classification is presented. It firstly uses the traditional discrete wavelet transform along with the hybrid Hoteling transform to obtain a fused imagery. Then a heuristic search algorithm is applied to search the best optimal harmony to generate the new principal components of the registered input images which is later classified using the K means support vector machines to build better classifiers for concealed weapon detection. Experimental results demonstrate the hybrid approach which shows the superior performance.
Co-Authors Abdullah Hasan Hussein Sabah Khudhair Abbas