Aggregation of fuzzy metrics and its application in image segmentation

被引：0

作者：

Ralevic, N. M. ^{[1
]}

Delic, M. ^{[1
]}

Nedovic, Lj. ^{[1
]}

机构：

[1] Univ Novi Sad, Fac Tech Sci, Dept Fundamentals Sci, Trg Dositeja Obradovica 6, Novi Sad 21000, Serbia

来源：

IRANIAN JOURNAL OF FUZZY SYSTEMS | 2022年 / 19卷 / 03期

关键词：

Aggregation functions; distance function; fuzzy metric; image segmentation; triangular conorms; triangular norms; DISTANCE FUNCTIONS; NORMS;

D O I：

暂无

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper proposes a novel method for the construction of a fuzzy metrics and demonstrates application in image segmentation. Some new properties of t-norms, t-conorms, aggregation functions, and fuzzy metrics are proved, which provides the procedures for constructing a new fuzzy metric. We prove that by applying some types of t-norms, t-conorms and aggregation functions on the sequence of fuzzy metrics, a new fuzzy metric could be obtained. The application of the fuzzy metric constructed in this way is illustrated in image segmentation by using the FCM algorithm. For the purpose of constructing a new fuzzy metric, an extended aggregation function called generalized quasi-arithmetic mean is considered.

引用

页码：19 / 37

页数：19

共 36 条

[1]

Bezdek J., 1999, FUZZY MODELS ALGORIT

[2] FCM - THE FUZZY C-MEANS CLUSTERING-ALGORITHM [J].