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Feature extraction method for digital images based on intuitionistic fuzzy local binary pattern

机译:基于直觉模糊局部二进制模式的数字图像特征提取方法

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Feature extraction is an important step in the field of digital image processing, which also helps in reducing the dimensions from large data. Researchers are investigating an efficient methods as there are lot of challenges in extracting significant features from an image that can reveal essential information. However, a very small work has been reported to this research domain in the last decades. In this paper, we propose intuitionistic fuzzy local binary (IFLBP) for extracting texture feature from the input image. The proposed technique extends fuzzy local binary pattern method by including intuitionistic fuzzy set theory in the demonstration of local patterns of texture in images. The proposed algorithm has been applied on various images and obtained result shows the effectiveness of our proposed technique.
机译:特征提取是数字图像处理领域的一个重要步骤,这也有助于减少大数据的尺寸。 研究人员正在调查有效的方法,因为在从可以揭示基本信息的图像中提取显着的特征时存在很多挑战。 然而,在过去的几十年中,已经向这一研究领域报告了一个非常小的工作。 在本文中,我们提出了从输入图像中提取纹理特征的直觉模糊本地二进制(IFLBP)。 所提出的技术通过在图像中局部纹理模式的示范中包括直觉模糊集理论来扩展模糊局部二进制模式方法。 所提出的算法已应用于各种图像,并获得结果显示了我们所提出的技术的有效性。

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