文章基本信息

标题：Robust Segmentation Based on Salient Region Detection Coupled Gaussian Mixture Model
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作者：Xiaoyan Pan ; Yuhui Zheng ; Byeungwoo Jeon 等
期刊名称：Information
电子版ISSN：2078-2489
出版年度：2022
卷号：13
期号：2
页码：98
DOI：10.3390/info13020098
语种：English
出版社：MDPI Publishing
摘要：The impressive progress on image segmentation has been witnessed recently. In this paper, an improved model introducing frequency-tuned salient region detection into Gaussian mixture model (GMM) is proposed, which is named FTGMM. Frequency-tuned salient region detection is added to achieve the saliency map of the original image, which is combined with the original image, and the value of the saliency map is added into the Gaussian mixture model in the form of spatial information weight. The proposed method (FTGMM) calculates the model parameters by the expectation maximization (EM) algorithm with low computational complexity. In the qualitative and quantitative analysis of the experiment, the subjective visual effect and the value of the evaluation index are found to be better than other methods. Therefore, the proposed method (FTGMM) is proven to have high precision and better robustness.