Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/18788
Title: An Enhanced Background Subtraction Algorithm for Smart Surveillance System Using Adaptive Gaussian Mixture Technique
Authors: Olaniyi, Olayemi Mikail
Bala, Jibril Abdullahi
Ganiyu, Shefiu Olusegun
Wisdom, Praise Emmanuel
Keywords: Background Subtraction
Motion Detection
Receiver Operating Characteristics
Short Message Service
Specificity
Sensistivity
Surveillance
Smart
Issue Date: 2020
Publisher: International Journal of Mechatronics, Electrical and Computer Technology (IJMEC)
Citation: Olayemi M. Olaniyi, Jibril A. Bala, Shefiu Olusegun Ganiyu and Praise Emmanuel. Wisdom. (2020). An Enhanced Background Subtraction Algorithm for Smart Surveillance System Using Adaptive Gaussian Mixture Technique. International Journal of Mechatronics, Electrical and Computer Technology (IJMEC)Vol. 10(38), Oct. 2020, PP. 4752-4761
Abstract: Surveillance is an important component of secure infrastructure. People need to ensure that their properties, homes, friends, families, and valuables are protected from intruders. In this article, we developed an enhanced background subtraction algorithm for smart surveillance of homes under changes in illumination. An adaptive Gaussian Mixture technique was applied to improve the conventional background subtraction technique for smart surveillance system by reducing false positives and improving the system performance in motion detection. The developed smart surveillance system has the ability to send notifications containing intruder’s image to registered email account and short message system to registered phone number whenever motion is detected. The performance evaluation of developed algorithm showed a sensitivity of 80%, specificity of 92% and an accuracy of 95.56%. This system works in conditions of illumination changes and can be adopted in motion detection for home surveillance.
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/18788
Appears in Collections:Mechatronics Engineering

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