| Issue |
MATEC Web Conf.
Volume 309, 2020
2019 International Conference on Computer Science Communication and Network Security (CSCNS2019)
|
|
|---|---|---|
| Article Number | 03029 | |
| Number of page(s) | 4 | |
| Section | Smart Algorithms and Recognition | |
| DOI | https://doi.org/10.1051/matecconf/202030903029 | |
| Published online | 04 March 2020 | |
An improved image segmentation algorithm based on the maximum class variance method
Beijing Institute of Graphic Communication, Beijing 102600
* Corresponding author: 1326174002@qq.com
Image segmentation is an important part of image processing. The result of image segmentation directly affects the effect of subsequent image processing. However the efficiency of the traditional maximum class variance method is low. This paper uses the cuckoo algorithm to optimize the traditional maximum class variance method to achieve a better segmentation effect. This image segmentation method combined with optimization theory can achieve the purpose of finding the optimal segmentation.
Key words: Maximum large class variance method / Cuckoo algorithm / Image segmentation / The image processing
© The Authors, published by EDP Sciences, 2020
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