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首页> 外文期刊>Journal of multiple-valued logic and soft computing >A Fuzzy Similarity Measure of Intuitionistic Fuzzy Sets for Color Image Retrieval Systems
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A Fuzzy Similarity Measure of Intuitionistic Fuzzy Sets for Color Image Retrieval Systems

机译:彩色图像检索系统直觉模糊集的模糊相似性度量

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摘要

In this paper a new scheme for image retrieval is proposed that represents color images by using the concepts of intuitionistic fuzzy sets while the concept of similarity is also characterized by fuzzy concepts. Color features that could be expressed in various color representation systems have been intensively used, independently or jointly, in image processing during the past decades. Fuzziness arises naturally from the imprecision or vagueness of the pixel color values and human perception. The Hue and Value in the HSV color space are used to construct the 2-D intuitionistic fuzzy sets. In the intuitionistic fuzzy sets, not only the membership degrees are considered but also the uncertainties that are involved in the non-membership degrees and are known as the hesitation measures are considered. The proposed similarity measure of intuitionistic fuzzy sets is a fuzzy quantity, rather than crisp quantity due to the vague concept of the similarities. Large-scale experiments demonstrate the robustness and effectiveness of the proposed scheme.
机译:本文提出了一种新的图像检索方案,该方案利用直觉模糊集的概念表示彩色图像,而相似性概念也以模糊概念为特征。在过去的几十年中,可以在各种颜色表示系统中表达的颜色特征已独立或联合用于图像处理中。模糊性自然是由像素颜色值的不精确性或模糊性以及人的感知引起的。 HSV颜色空间中的色相和值用于构建二维直觉模糊集。在直觉模糊集中,不仅考虑了隶属度,而且还考虑了非隶属度所涉及的不确定性,这些不确定性被称为犹豫措施。直觉模糊集的拟议相似性度量是模糊量,而不是由于相似性概念含糊的清晰量。大规模实验证明了该方案的鲁棒性和有效性。

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