Research on the algorithm of electromagnetic leakage reduction and sequence of image migration feature retrieval

Chunwei Miao,Jianlin Hu

doi:10.1186/s13640-019-0430-y

Abstract

When the computer is working, it will transmit the electromagnetic leakage signal containing the video information and receive and process the electromagnetic leakage signal within a certain distance, which can reproduce the screen information and form the electromagnetic leakage restoration sequence image. Due to the noise in the receiving process and the fluctuation of the video line and field signal, the image of the electromagnetic leakage restoration sequence will be blurred and will drift between frames. The multi-frame cumulative averaging method can theoretically improve the signal-to-noise ratio of the reconstructed image, but the offset of the reconstructed image sequence caused by the electromagnetic leakage will bring adverse effects. Firstly, this paper analyzes the noise of electromagnetic leakage emission and restoration sequence images and the method of multi-frame cumulative averaging, as well as the cumulative averaging effect of multi-frame sequence images under the influence of image offset. Secondly, on the basis of theoretical analysis, an algorithm of image migration feature retrieval for electromagnetic leakage restoration sequence is proposed and validated, which achieves more accurate inter-frame matching, automatic offset calculation, and multi-frame sequence image accumulation and enhances the recognition of the electromagnetic leakage restoration image. Lastly, different algorithms are compared, and their effects are evaluated as well.

Highlights

The changes of current during the process of a working computer will generate electromagnetic leakage emission
5 Conclusions In this paper, the principle of video electromagnetic leakage emission reduction is briefly introduced, and the multi-frame accumulation average method is proposed based on the noise characteristics of sequence images
In order to correct the image migration, this paper analyzed the characteristics of sequence images, proposed the image migration feature retrieval algorithm and the implementation steps, and used the correlation between sequence images to verify the effectiveness of the image migration feature retrieval algorithm

Summary

Introduction

The changes of current during the process of a working computer will generate electromagnetic leakage emission. Aiming at the problems of slow image processing speed and poor real-time capability and accuracy of feature point matching in mobile robot vision-based SLAM, Zhu proposes a novel image matching method based on color feature and improved SURF algorithm [16]. Olson improve upon these using a probabilistic formulation for image matching in terms of maximum-likelihood estimation that can be used for both edge template matching and gray-level image matching [17]. Different algorithms are compared, and their effects are evaluated as well

Results

Discussion

Conclusion