JOURNAL ARTICLE

A real time abandoned object detection hardware approach

Abstract

Most of the bomb blast was done with the help of abandoned objects, so effective and efficient detection and Real time localization of abandoned objects is very important to prevent attacks. This paper presents an effective hardware implementation approach or Abandoned Object Detection in video surveillance. We had combined long term and short term background model for foreground extraction. Change detection is done with the help of fuzzy clustering using log ratio and mean ratio operators. In proposed system SVM classifier is used to classify detected static object and its location is traced by GPS, further alter process is handled by embedded module. Overall communication is done through Internet of Things (IoT).

Keywords:
Computer science Object detection Cluster analysis Support vector machine Feature extraction Artificial intelligence Fuzzy logic Object (grammar) Computer vision Process (computing) Classifier (UML) Global Positioning System Real-time computing Pattern recognition (psychology) Operating system

Metrics

4
Cited By
0.13
FWCI (Field Weighted Citation Impact)
15
Refs
0.55
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

IoT-based Smart Home Systems
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Advanced Chemical Sensor Technologies
Physical Sciences →  Engineering →  Biomedical Engineering
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