Storage Optimization using Adaptive Thresholding Motion Detection
Received: 16 November 2020 | Revised: 9 December 2020 | Accepted: 14 December 2020 | Online: 11 April 2021
Corresponding author: F. Akhtar
Abstract
Data storage is always an issue, especially for video data from CCTV cameras that require huge amounts of storage. Moreover, monitoring past events is a laborious task. This paper proposes a motion detection method that requires fewer calculations and reduces the required data storage up to 70%, as it stores only the informative frames, enabling the security personnel to retrieve the required information more quickly. The proposed method utilized a histogram-based adaptive threshold for motion detection, and therefore it can work in variable luminance conditions. The proposed method can be applied to streamed frames of any CCTV camera to efficiently store and retrieve informative frames.
Keywords:
storage optimization, adaptive threshold, motion detection, video miningDownloads
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