| 基于形态学重建改进的FCM算法 |
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| 引用本文：候慧?覮，李水艳.基于形态学重建改进的FCM算法[J].计算技术与自动化,2020,(1):93-96 |
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| 中文摘要:传统的FCM（fuzzy c-means）算法可以准确的分割多数无噪声图像，但对噪声图像非常敏感。针对于此类问题，提出了一种基于形态学重建的改进FCM算法。首先利用形态学闭合重建算子对含噪图像进行光滑化。然后利用基于邻域信息的改进FCM算法对合成图像及医学图像进行分割处理，最终得出了更加精确的分割结果。通过与其它两类算法进行数值实验对比，验证了所提出算法的有效性和实用性。 |
| 中文关键词:图像分割 形态学重建 模糊c均值算法 |
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| Improved FCM Algorithm Based on Morphological Reconstruction |
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| Abstract:The traditional fuzzy c-means（FCM） algorithm can segment noiseless images accurately，but it is very sensitive to noise. Aiming at such problems，an improved FCM algorithm based on morphological reconstruction is proposed. First，the morphological closing reconstruction operator is used to smooth the noisy image. Then，the improved FCM algorithm designed by the neighborhood information is used to segment the composite image and the medical image. Finally，we get more accurate segmentation results. The effectiveness and practicability of the proposed algorithm are verified by numerical experiments with other two types of algorithms. |
| keywords:image segmentation morphological reconstruction fuzzy c-means algorithm |
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