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Image Enhancement using Thermal-visible Fusion for Human Detection

Ezrinda, Mohd Zaihidee and Kamarul Hawari, Ghazali and Mohd Zuki, Salleh (2017) Image Enhancement using Thermal-visible Fusion for Human Detection. In: Journal of Physics: Conference Series, 1st International Conference on Applied & Industrial Mathematics and Statistics 2017 (ICoAIMS 2017), 8-10 August 2017 , Kuantan, Pahang, Malaysia. pp. 1-6., 890 (012038). ISBN 1742-6596

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Abstract

An increased interest in detecting human beings in video surveillance system has emerged in recent years. Multisensory image fusion deserves more research attention due to the capability to improve the visual interpretability of an image. This study proposed fusion techniques for human detection based on multiscale transform using grayscale visual light and infrared images. The samples for this study were taken from online dataset. Both images captured by the two sensors were decomposed into high and low frequency coefficients using Stationary Wavelet Transform (SWT). Hence, the appropriate fusion rule was used to merge the coefficients and finally, the final fused image was obtained by using inverse SWT. From the qualitative and quantitative results, the proposed method is more superior than the two other methods in terms of enhancement of the target region and preservation of details information of the image.

Item Type: Conference or Workshop Item (Speech)
Uncontrolled Keywords: video surveillance, multisensory image fusion, human detection, Stationary Wavelet Transform
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty/Division: Faculty of Electrical & Electronic Engineering
Faculty of Industrial Sciences And Technology
Depositing User: Puan Ezrinda Mohd Zaihidee
Date Deposited: 30 Jan 2018 04:14
Last Modified: 29 Jun 2018 01:11
URI: http://umpir.ump.edu.my/id/eprint/19856
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