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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Acknowledgements
I would like to express my supreme appreciation to Ms. Usha Mittal for her unceasing help with the paper.
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Kaur, L., Mittal, U. (2019). Moving Object Recognition and Detection Using Background Subtraction. In: Kumar, A., Mozar, S. (eds) ICCCE 2018. ICCCE 2018. Lecture Notes in Electrical Engineering, vol 500. Springer, Singapore. https://doi.org/10.1007/978-981-13-0212-1_1
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DOI: https://doi.org/10.1007/978-981-13-0212-1_1
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