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2019 | OriginalPaper | Chapter

Moving Object Recognition and Detection Using Background Subtraction

Authors : Loveleen Kaur, Usha Mittal

Published in: ICCCE 2018

Publisher: Springer Singapore

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Abstract

Motion detection and object recognition algorithms are a significant research area in computer vision and involve building blocks of numerous high-level methods in video scrutiny. In this paper, a methodology to identify a moving object with the use of a motion-based segmentation algorithm, i.e. background subtraction, is explained. First, take a video as an input and to extract the foreground from the background apply a Gaussian mixture model. Then apply morphological operations to enhance the quality of the video because during capture the quality of a video is degraded due to environmental conditions and other factors. Along with this, a Kalman filter is used to detect and recognize the object. Finally, vehicle counting is complete. This method produces a better result for object recognition and detection.

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next chapter Fog Computing: Overview, Architecture, Security Issues and Applications
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Metadata
Title
Moving Object Recognition and Detection Using Background Subtraction
Authors
Loveleen Kaur
Usha Mittal
Copyright Year
2019
Publisher
Springer Singapore
Book
ICCCE 2018

Print ISBN: 978-981-13-0211-4

Electronic ISBN: 978-981-13-0212-1

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-981-13-0212-1_1