【摘要】 通过分析凝胶蛋白图像的特点,提出一种基于模糊核C均值聚类(KFCM)分割算法的改进算法。首先使用引导滤波器对图像进行滤波并增强图像对比度,然后通过KFCM算法对图像聚类,最后采用最大隶属原则去模糊化,实现最优分割,在此过程中引入样本方差来计算σ值。凝胶蛋白图像分割实验表明,算法具有更好的自适应性和分割精度。更多还原

【Abstract】 An improved algorithm based on kernel fuzzy C-means clustering segmentation algorithm(KFCM)is proposed by analysis of the characteristics of protein gel image.First,the guide filter is used to enhance the image contrast.Then the KFCM algorithm is used for the image clustering.Finally,the maximum membership principle is applied for de-blurring and the optimal segmentation.In this process,the sample variance is introduced to calculate the value of sigma.Experiment results show that the algorithm has better adaptability and segmentation accuracy.更多还原