文章基本信息

标题：An improved image segmentation algorithm based on the maximum class variance method
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作者：Qianhui Qi ; Yimin Tian ; Lili Han 等
期刊名称：MATEC Web of Conferences
电子版ISSN：2261-236X
出版年度：2020
卷号：309
页码：1-4
DOI：10.1051/matecconf/202030903029
语种：English
出版社：EDP Sciences
摘要：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.
关键词：Keywords:enMaximum large class variance methodCuckoo algorithmImage segmentationThe image processing