Use of intuitionistic fuzzy set methods in parallel classification of image data

A. Michalíková, A. Dudáš
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Abstract

Image classification is process of allocation of image data entities to classes in such a way, that individual elements of a class bear common features. We are focusing on the methods of tire tread image data classification based on intuitionistic fuzzy sets and voting mechanism. The paper presents the design, implementation and experimental evaluation of parallel algorithms for classification of tire tread images based on intuitionistic fuzzy set methods which include similarity measure, distance function and chosen intuitionistic fuzzy negations.
直觉模糊集方法在图像数据并行分类中的应用
图像分类是将图像数据实体分配到类的过程,使类中的单个元素具有共同的特征。研究了基于直觉模糊集和投票机制的轮胎胎面图像数据分类方法。提出了一种基于直觉模糊集方法的轮胎胎面图像分类并行算法的设计、实现和实验评价,该算法包括相似度量、距离函数和选择的直觉模糊否定。
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