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Foreground Extraction Using Hilbert-Schmidt Independence Criterion and Particle Swarm Optimization Independent Component Analysis

Publish Year: 1399
Type: Journal paper
Language: English
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Document National Code:

JR_IJE-33-5_036

Index date: 14 June 2020

Foreground Extraction Using Hilbert-Schmidt Independence Criterion and Particle Swarm Optimization Independent Component Analysis abstract

Foreground extraction is one of the crucial subjects in image processing, which drives different applications in industry. The reality behind the continuous research in this area is the various challenging problems we encounter during the separation process of foreground and background images. Among the source separation approaches, the independent component analysis (ICA) is the most prevalent, being involved in different areas of signal separation applications. Despite the improvements being achieved in foreground extraction, the sudden luminance variations and background movements adversely impact the results of techniques in this regard. In this paper, a novel structure called HSIC_ICA is introduced to address the mentioned problem using a modified version of the ICA algorithm which, leverages the Hilbert-Schmidt Independence Criterion (HSIC) instead of the common objective functions.  Moreover, the unmixing matrix elements of ICA are extracted through a Particle Swarm Optimization (PSO) evolutionary algorithm in a much faster way. The experimental results clearly show that the proposed method outperforms over the significant works being cited among the references, using Wallflower dataset.

Foreground Extraction Using Hilbert-Schmidt Independence Criterion and Particle Swarm Optimization Independent Component Analysis Keywords:

Foreground Extraction Hilbert , Schmidt Independence Criterion Independent Component Analysis Particle Swarm Optimization Unsupervised Method

Foreground Extraction Using Hilbert-Schmidt Independence Criterion and Particle Swarm Optimization Independent Component Analysis authors

H. Mahdian Toroghi

Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

M. Mirzarezaee

Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

B. Najar Araabi

Machine Learning and Computational Modeling Labruatory, College of Engineering, University of Tehran, Tehran, Iran