Research Article
Remote consultation image stitching method based on wireless sensor technology and mathematical morphology
@ARTICLE{10.4108/eetpht.v8i31.700, author={Xiaoge Li}, title={Remote consultation image stitching method based on wireless sensor technology and mathematical morphology}, journal={EAI Endorsed Transactions on Pervasive Health and Technology}, volume={8}, number={31}, publisher={EAI}, journal_a={PHAT}, year={2022}, month={7}, keywords={wireless sensor technology, mathematical morphology, image stitching, image acquisition, image denoising, image registration}, doi={10.4108/eetpht.v8i31.700} }
- Xiaoge Li
Year: 2022
Remote consultation image stitching method based on wireless sensor technology and mathematical morphology
PHAT
EAI
DOI: 10.4108/eetpht.v8i31.700
Abstract
INTRODUCTION: In order to obtain seamless and high-precision remote consultation image mosaic results, a remote consultation image mosaic method based on wireless sensor technology and mathematical morphology is studied. A consultation image acquisition unit based on wireless sensor technology is designed, and the remote consultation image signal is collected by sensor; In the process of signal conditioning, a filter based on mathematical morphology is used to reduce the influence of noise on the accuracy of remote consultation image acquisition. OBJECTIVES: Compressed sensing technology is used to realize the compression, transmission and recovery of consultation image sampling data. METHODS: After preprocessing the image through shadow correction, surf algorithm is used to construct the scale space to determine the main direction of feature points in the image; The extended surf descriptor is constructed based on feature points for consultation image registration. RESULTS: Based on the spatial transformation relationship between images, the improved gradual in and gradual out stitching method is used to complete the remote consultation image stitching. Experimental results show that this method can accurately collect consultation image signals, and the corresponding rate of the feature point extraction results reaches nearly 99%, which is relatively robust. CONCLUSION: The RMSE error of the image registration results is less than 2.692, which improves the accuracy of the remote consultation image stitching results, well solves the problem of image visual field reduction, and there is no seam in the stitching area.
Copyright © 2022 Li Xiaoge, licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.