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-ADMM Algorithm for Sparse Image Recovery Under Impulsive Noise Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Research on Vectorization Method of Complex Linear Image Data

Authors : Jinbao Shan, Weiwei Jiang

Published in: Advanced Hybrid Information Processing

Publisher: Springer International Publishing

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Abstract

The traditional data extraction method of complex linear pixel image data can not cope with the vibration and noise of data in the process of data vectorization, which causes the problem of low accuracy of the extraction results. To solve this problem, a complex vector image extraction method is proposed. The MATLAB method is used to remove the noise of complex linear pixel images. In this way, the preprocessing of complex linear pixel image data is provided as the condition of segmentation. The two value algorithm is used to segment the complex linear pixel image data, and the minimum value of the target function is calculated. The data curves are drawn according to the calculation results. Vectorization of image data. The experimental results of the simulated application environment design show that the accuracy of the extraction result is about 45% compared with the traditional extraction method when the same image data is used.

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previous chapter Parallel Implementation and Optimization of a Hybrid Data Assimilation Algorithm
next chapter Modeling Analysis of Intelligent Logistics Distribution Path of Agricultural Products Under Internet of Things Environment
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Metadata
Title
Research on Vectorization Method of Complex Linear Image Data
Authors
Jinbao Shan
Weiwei Jiang
Copyright Year
2019
Book
Advanced Hybrid Information Processing

Print ISBN: 978-3-030-19085-9

Electronic ISBN: 978-3-030-19086-6

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-19086-6_35

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