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Mobile Networks and Applications
Published in: Mobile Networks and Applications 3/2022

21-08-2021

Application of SVM and its Improved Model in Image Segmentation

Authors: Aimin Yang, Yunjie Bai, Huixiang Liu, Kangkang Jin, Tao Xue, Weining Ma

Published in: Mobile Networks and Applications | Issue 3/2022

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Abstract

In the research and application of images, people are often only interested in the foreground or specific area of the image, so it is necessary to extract the specific area from the image, and image segmentation technology is the key to solving this problem. Aiming at the complex background and the color image with unclear target contour as the target image to be segmented, this paper first uses the texture and color of the image as the feature vector, and proposes an image segmentation algorithm based on SVM. The experimental results show that the segmentation accuracy is 91.23%. Secondly, in order to improve the accuracy of segmentation, the SVM algorithm is improved. The improved SVM algorithm is based on the grid search method to optimize the parameters C and g in the SVM. At the same time, the HIS color channel is added to the feature vector to obtain more Excellent SVM image segmentation model. Finally, the color image segmentation is verified and compared with the standard SVM algorithm. The experimental results show that the accuracy rate of the improved SVM algorithm reaches 97.263%, which improves the segmentation efficiency. It is verified that the improved model proposed in this paper can effectively segment complex color images.
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Metadata
Title
Application of SVM and its Improved Model in Image Segmentation
Authors
Aimin Yang
Yunjie Bai
Huixiang Liu
Kangkang Jin
Tao Xue
Weining Ma
Publication date
21-08-2021
Publisher
Springer US
Published in
Mobile Networks and Applications / Issue 3/2022
Print ISSN: 1383-469X
Electronic ISSN: 1572-8153
DOI
https://doi.org/10.1007/s11036-021-01817-2

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