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On edge detection based on new intuitionistic fuzzy divergence and entropy measures

机译:基于新的直观模糊分歧和熵措施的边缘检测

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Edges of the image plays an important role in the field of digital image processing and computer vision. It reduces the amount of data, extract useful information from the image and also preserve significant structural properties of an input image. Further, it can be used in object and facial expression detection. In this paper, we have proposed new intuitionistic fuzzy divergence and entropy measures with its proof of validity for an intuitionistic fuzzy sets. A new and significant technique has been developed for edge detection. The proposed method has been demonstrated on various sample images. The detected edges of the sample images are true, smooth and sharpen which is found to be better than existing methods.
机译:图像的边缘在数字图像处理和计算机视野领域起着重要作用。它减少了数据量,从图像中提取有用信息,并且还保留输入图像的显着结构特性。此外,它可以用于对象和面部表情检测。在本文中,我们提出了新的直观模糊分歧和熵措施,其有效性的直观模糊套件。已经开发了一种新的和重要的技术,用于边缘检测。已经在各种样本图像上证明了所提出的方法。检测到的样本图像的边缘是真的,平滑和锐化,其被发现比现有方法更好。

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