A competition in unsupervised color image segmentation

被引：16

作者：

Haindl, Michal ^{[1
]}

Mikes, Stanislav ^{[1
]}

机构：

[1] Acad Sci Czech Republ, Inst Informat Theory & Automat, CR-18208 Prague, Czech Republic

来源：

PATTERN RECOGNITION | 2016年 / 57卷

关键词：

Unsupervised image segmentation; Segmentation contest; Texture analysis; TEXTURE; MODEL; CUTS;

D O I：

10.1016/j.patcog.2016.03.003

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A competition in unsupervised color image segmentation took place in conjunction with the 22nd International Conference on Pattern Recognition (ICPR 2014). It aimed to promote evaluation of unsupervised color image segmentation algorithms using publicly available data sets, and to allow for any subsequent methods to be easily evaluated and compared with the results of the contested methods under identical conditions. Our comparison of different methods is based on the standard methodology of performance assessment using an on-line verification server. We present in this paper the evaluation of the top six results submitted to the ICPR 2014 contest in unsupervised color image segmentation and compare them with 11 other state-of-the-art unsupervised image segmenters. (C) 2016 Elsevier Ltd. All rights reserved.

引用

页码：136 / 151

页数：16

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