Digital Image Automatic Recognition and Tracking Based on Electronic Derotation Algorithm

Meirong Gao

doi:10.1155/2021/6111812

Abstract

With the continuous development of my country’s social economy, the ways to acquire images have become more and more abundant. How to effectively process, manage, and mine images has become a major and difficult problem in research. In view of the difficult problem of image recognition, the electronic derotation algorithm is introduced in this study, by combing and monitoring the edge features, establishing a corresponding sample database, analyzing the edge features of the image, and performing effective and stable tracking, so as to realize the automatic recognition and tracking of the digital image. The simulation experiment results show that the electronic derotation algorithm is effective and can support the automatic recognition and tracking of digital images.

Highlights

With the continuous development of my country’s society and economy, the methods for acquiring digital images have been greatly improved, such as traditional photography, modern remote sensing photography, and other technologies, but how to process the acquired images and information mining have become important research hotspots and difficulties [1,2,3,4,5]
Cubic Convolution Interpolation Method. is method essentially uses the cubic sampling function S(ω) for interpolation approximation and uses 16 points around the sample for sampling interpolation. e cubic function is used for approximation, which brings high complexity calculations, the long calculation time, which is not suitable for real-time processing of the image. Each of these three methods has its own advantages and disadvantages. e specific method of image electronic derotation needs to be selected according to actual needs, while considering the comprehensive hardware conditions
From the error position curve, it can be seen that it is compared with the actual position. e error is very small; this is through the threshold segmentation of the digital image, and the normalized calculation of the image is realized. e corresponding algorithm is used to identify the initial position of the moving image, and at the same time, the calculation function of the tracking target is obtained through the electronic derotation algorithm and the mean value theory to realize the tracking and positioning of the position

Summary

Introduction

With the continuous development of my country’s society and economy, the methods for acquiring digital images have been greatly improved, such as traditional photography, modern remote sensing photography, and other technologies, but how to process the acquired images and information mining have become important research hotspots and difficulties [1,2,3,4,5]. Erefore, whether it is a forward or reverse rotation, all the pixel values of the image can be calculated by reasoning using the above process, so as to determine the position of the pixel, but it should be noted that except for the initial pixel needing floating point multiplication, the rest of the subsequent calculations are completed by floating point addition, which saves calculation time and improves calculation efficiency. E cubic function is used for approximation, which brings high complexity calculations, the long calculation time, which is not suitable for real-time processing of the image. Each of these three methods has its own advantages and disadvantages. Each of these three methods has its own advantages and disadvantages. e specific method of image electronic derotation needs to be selected according to actual needs, while considering the comprehensive hardware conditions

Automatic Recognition and Tracking of Image

Result output

Findings

Conclusions