Image processing analysis of sigmoidal Hadamard wavelet with PCA to detect hidden object - Altaher, Ammar Wisam; Abbas, Sabah Khudhair (Telkomnika, 2020)
Received Jul 9, 2019 Revised Jan 29, 2020 Accepted Feb 26, 2020 Keywords: Concealed weapon detection IR image Principle component analysis Sigmoidal Hadamard Support vocter machine 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. [...]multiple-sensor image fusion of visual and infrared images has been tested extensively [9, 10]. After this compute eigenvalues and eigen process vectors for Hadamard-DWT, then find PCA of the coefficients processing of decomposing, apply fusion rule by multiplying the principal components with the Hadamard-DWT decomposed Coefficients and fuse them together, Apply Inverse DWT and inverse Hadamard transform to get the fused image, Subject the Fused Image to a concealed weapon detection system, perform clustering using K-means algorithm on the fused image, extract features of the fused image and Use SVM classifier to detect whether a weapon is concealed or not. 3.2. The fused image obtained from the sigmoidal Hadamard wavelet transform with PCA is then given to a concealed weapon detection system to detect the hidden weapon. 3.3.Hadamard Transform These are special cases of Fourier Transforms which perform symmetric, linear, orthogonal and complex operations.