Extended power-based aggregation of distance functions and application in image segmentation

被引:10
作者
Delic, Marija [1 ]
Nedovic, Ljubo [1 ]
Pap, Endre [2 ]
机构
[1] Univ Novi Sad, Fac Tech Sci, Dept Fundamentals Sci, Trg Dositeja Obradovica 6, Novi Sad 21000, Serbia
[2] Singidunum Univ, Dept Postgrad Studies, 32 Danijelova St, Belgrade 11000, Serbia
关键词
Distance function; Metrics; Extended aggregation function; Local binary pattern; Image segmentation; Fuzzy c-Means algorithm; CLASSIFICATION; OPERATORS;
D O I
10.1016/j.ins.2019.04.053
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we psropose a novel method for construction of a distance function and demonstrate its application in image segmentation. In algorithms for image segmentation, distance functions represent a criterion which divides pixels into groups of segments. We introduce two extended aggregation functions, extended powers product and extended weighted arithmetic mean of powers. Their relevant properties are examined, as well as certain resulting properties of distance functions, which are constructed by an application of mentioned aggregation functions. In addition, one pixel descriptor, which is motivated by Local Binary Pattern family of descriptors (LBPs), is introduced and discussed. In the experimental section, we present an application of the introduced extended aggregation functions and descriptor, by a construction of a new distance function, used in Fuzzy c-Means Clustering Algorithm (FCM) for image segmentation. (C) 2019 Elsevier Inc. All rights reserved.
引用
收藏
页码:155 / 173
页数:19
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