基于烟花算法的多级图像阈值分割

M. Tuba, N. Bačanin, Adis Alihodžić
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引用次数: 66

摘要

本文介绍了一种针对多级图像阈值问题调整的最新fireworks算法的实现。这是一个重要的问题,因为它经常用于图像处理,以达到图像分割的目的。由于可能的阈值组合的数量随着理想阈值的数量呈指数增长,标准确定性方法在处理该问题时不能产生令人满意的结果。为了测试我们提出的方法的性能,我们在标准基准图像上使用Kapur的最大熵阈值函数,其中从穷举搜索中已知最优解(最多五个阈值点)。结果表明,该方法在该领域具有很大的应用潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multilevel image thresholding by fireworks algorithm
This paper presents implementation of the recent fireworks algorithm adjusted for solving multilevel image thresholding problem. This is an important problem since it is often used in image processing for the purpose of image segmentation. Since the number of possible threshold combinations grows exponentially with the number of desirable thresholds, standard deterministic methods could not generate satisfying results when tackling this problem. To test the performance of our proposed approach, we employed Kapur's maximum entropy thresholding function on standard benchmark images where the optimal solutions are known (up to five thresholding points) from the exhaustive search. Results show that our approach has great potential in this field.
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