Application of Target Image Recognition Based on Network Sensitive Information Filtering Technology

Authors

  • Xiaohong Li Department of Adult Education, Hebei Vocational University of Industry and Technology, Shijiazhuang 050000, China
  • Guiying Duan Department of Computer Technology, Hebei Vocational University of Industry and Technology, Shijiazhuang 050000, China
  • Fang Tian Department of Computer Technology, Hebei Vocational University of Industry and Technology, Shijiazhuang 050000, China

Abstract

In order to improve the detection ability of target images under network sensitive information interference, a road surface target image recognition method based on deep fusion filtering is proposed. This method is comprised of the following steps: analyzing the action characteristic quantity of a road surface target image under the interference of network sensitive information, collecting the road surface target image under the interference of the network sensitive information by adopting a block combined monitoring technology, detecting the edge contour of the collected road surface target image under the interference of the network sensitive information, performing deep integration analysis and feature extraction of the road surface target image under the interference of the network sensitive information by combining the image segmentation technology. The gray histogram distribution structure model of road surface target image under network sensitive information interference is constructed, the effective extraction of the road surface target image and corner information under network sensitive information interference is carried out by adopting a region block matching method, the road surface target image under network sensitive information interference is simulated by adopting a multi-dimensional pixel reconstruction method, the characteristic point calibration and detection of the road surface target image under network sensitive information interference are carried out by adopting a large interval nearest neighbor specific point calibration method, and the optimal identification of the road surface target image under network sensitive information interference is realized. The simulation results show that this method has higher accuracy and better feature recognition ability for road surface target image recognition under network sensitive information interference and improves the road surface target image recognition ability under network sensitive information interference.

Keywords: Network Sensitive Information; Filtering; Target Image; Recognition.

Cite As

X. Li, G. Duan and F. Tian, "Massive Real-Time Data Mining Algorithm for a Multimedia Database", Engineering Intelligent Systems, vol. 30 no. 2, pp. 93-103, 2022.

 

 

 

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Published

2022-03-01

Issue

Vol. 30 No. 2 (2022): International Journal of Engineering Intelligent Systems

Section

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