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Image Segmentation Based on Two-dimensional Cloud Model

机译:基于二维云模型的图像分割

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摘要

There are many uncertainties in image segmentation, which should be handled by theories and methods with uncertainty. Cloud model is a kind of effective method to handle uncertainty, which considers fuzziness, randomness and the connection of them. Image segmentation based on one-dimensional cloud model processes the one-dimensional grayscale histogram, and segments images using one-dimensional cloud transformation and synthesis, but does not consider spatial information of images. The paper proposes a method based on two-dimensional cloud model, which processes two-dimensional grayscale histogram, and segments images using two-dimensional cloud transformation and synthesis. The proposed method considers spatial information of images, and has good performance suppressing noise. Results of many experiments indicate that the proposed method obtains better effect than those of traditional methods, and it is feasible and effective.
机译:图像分割中存在很多不确定性,应采用具有不确定性的理论和方法来处理。云模型是一种处理不确定性的有效方法,它考虑了模糊性,随机性以及它们之间的联系。基于一维云模型的图像分割处理一维灰度直方图,并使用一维云变换和合成对图像进行分割,但不考虑图像的空间信息。提出了一种基于二维云模型的方法,该方法处理二维灰度直方图,并通过二维云变换和合成对图像进行分割。该方法考虑了图像的空间信息,具有良好的降噪性能。大量实验结果表明,该方法取得了比传统方法更好的效果,是可行,有效的。

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