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Public Security Video Image Detection System Construction Platform in Cloud Computing Environment

The public security image detection system is an important way to assist the police in the investigation. In today’s cloud computing environment, the processing power of cloud computing is gradually improving. In order to explore its application in the investigation system, this paper constructs a p...

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Bibliographic Details
Published in:Computational intelligence and neuroscience 2022-02, Vol.2022, p.4113803-13
Main Author: Yin, Hexiao
Format: Article
Language:English
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Summary:The public security image detection system is an important way to assist the police in the investigation. In today’s cloud computing environment, the processing power of cloud computing is gradually improving. In order to explore its application in the investigation system, this paper constructs a public security video image investigation system based on cloud computing environment. This paper uses cloud computing technology to improve the processing capacity of the system. It then combines the storage capabilities of the backend server implementation technology and the working principle of Hadoop to construct a basic model. Then combined with the storage capability of the backend server implementation technology and the working principle of Hadoop and CP-ABE encryption, decryption, and reconstruction, a basic model is constructed. This paper also designs public security video surveillance system vehicle detection and test experiments, cloud storage encryption algorithm experiments, and computational storage requirements analysis experiments. It optimizes the system based on the results of the experiment and finally compares it with the traditional investigation system. The experimental results show that the public security video image detection system based on cloud computing can improve the accuracy by 5%–25% compared with the traditional detection system. And the public security video image detection system based on cloud computing can increase the efficiency by 2%–17% compared with the traditional detection system.
ISSN:1687-5265
1687-5273
DOI:10.1155/2022/4113803