| 基于高斯统计模型的快速图像区域分割方法 |
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| 引用本文： | 胡小丹,李文,刘海博. 基于高斯统计模型的快速图像区域分割方法[J]. 福建师范大学学报(自然科学版), 2011, 27(2): 133-137 |
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| 作者姓名： | 胡小丹 李文 刘海博 |
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| 作者单位： | 福建师范大学物理与光电信息科技学院,福建,福州,350007 |
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| 摘 要： | 目前很多图像分割方法不能满足图像信息生成的随机性以及面对应用的实时性.提出一种基于高斯统计模型的快速图像区域分割算法,与已有的一些图像区域分割算法相比,该方法不用图像去噪,直接利用噪声建立高斯统计模型,还采用最大最小值的方法,提出初始分割的思想.实验结果表明新方法增强了分割结果的稳定性,提高了分割速度,更加符合了图像要...
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| 关 键 词： | 高斯统计模型 噪声 最大最小值 图像区域分割 |
A Fast Image Region Segmentation Method Based on Gaussion Statistical Model |
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| HU Xiao-dan,LI Wen,LIU Hai-bo. A Fast Image Region Segmentation Method Based on Gaussion Statistical Model[J]. Journal of Fujian Teachers University(Natural Science), 2011, 27(2): 133-137 |
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| Authors: | HU Xiao-dan LI Wen LIU Hai-bo |
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| Affiliation: | HU Xiao-dan,LI Wen,LIU Hai-bo(School of Physics and OptoElectronics Technology,Fujian Normal University,Fuzhou 350007,China) |
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| Abstract: | According to the randomness of image information and the timeliness of facing application,a fast image region segmentation algorithm based on the Gaussion statistical model is introduced in this paper.Compared with some existed image region segmentation algorithms,the method which this article proposed establishes the Gaussion statistical model using the noise instead of image denoising.Besides,max-min method is also used in this article and the initial division thought is proposed.The experiments indicate ... |
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| Keywords: | Gaussian statistical model noise max-min value image region segmentation |
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