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Dynamic strategy to use optimum memory space in real-time video surveillance

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Abstract

In present days real-time video surveillance is a very essential aspect of establishing safety, observing traffic, and detecting violence and crimes. Intelligent video surveillance (IVS) is one of the most acknowledged frameworks in a security application. But, video surveillance systems consume huge memory space to store the recorded video, especially in the case of high-resolution recording. However, if we use low-resolution video recording then the video quality will be reduced and the objects/violence cannot be identified clearly. To overcome the stated limitation, this article introduced a smart video surveillance system with a dynamic strategy to use optimum memory space with the best surveillance objective. The proposed system can dynamically record video with high-resolution during suspicious movement of objects/violence as well as low-resolution video at other times. The system is based on the detection of suspicious movement of objects in consecutive frames, saving of suspicious frames with high resolution, and neglecting of less important frames. Finally, the Contrast Limited Adaptive Histogram Equalization (CLAHE) based on Color Channel is applied to all the suspicious frames as a post-processing step for better contract adjustment and to provide a clear view of suspicious objects in frames. The quality of enhanced frames are assessed by two no-reference methods, i.e. NIQMC and BIQME. Multiple visual quality parameters like sharpness, contrast, colorfulness, brightness, and naturalness of frames, etc. are used for assessment Several real-time experiments reveal that the proposed system can detect suspicious objects with 97.65% accuracy. Besides, it consumes 75% less memory space in real-time surveillance.

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Acknowledgements

The authors would like to acknowledge the National Institute of Technology Agartala, Tripura, India for providing a world-class research environment including the research laboratory.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology Agartala, Agartala, Tripura, India

    Tamal Biswas, Diptendu Bhattacharya & Gouranga Mandal

  2. School of Computer Science and Engineering, VIT-AP University, Amaravati, Andhra Pradesh, India

    Gouranga Mandal

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  1. Tamal Biswas
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Biswas, T., Bhattacharya, D. & Mandal, G. Dynamic strategy to use optimum memory space in real-time video surveillance. J Ambient Intell Human Comput 14, 2771–2784 (2023). https://doi.org/10.1007/s12652-023-04521-z

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