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A Comparative Study of different Image Preprocessing Methods used for Multiple Car Detection and Tracking
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| Author:
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NEELIMA SATHEESH, S. SUSHMITHA, V. KANCHANA
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| Abstract:
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Multiple car detection and recognition using video surveillance system is a difficult problem in image processing. Multiple car detection helps to reduce traffic congestion’s in highway, reduce road accidents, identifying suspicious vehicles, identifying people in crime scenes etc. There are several methods already existing in the field of vehicle detection, and most of them are highly expensive and unreliable. To overcome this, we have proposed more efficient and economic system which provides accurate results. For this, conversion of video into different frames has been carried out as the initial step, followed by effective pre-processing, which is a crucial part in image processing, it effectively improves all other processes that takes input from prepossessed data for further analysis. Therefore by making prepossessing steps more robust, we will be able to get more accurate and reliable outputs. After obtaining the pre-processed data, different segmentation methods has been applied, which will help in detection and recognition of vehicles in traffic.
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| Keyword:
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Multiple Car Detection, Image processing, Pre-processing, Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Maximum Difference(MD).
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| EOI:
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| DOI:
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https://doi.org/10.31838/ijpr/2020.12.04.161
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| Download:
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