RELAXED ORIENTED IMAGE FORESTING TRANSFORM FOR SEEDED IMAGE SEGMENTATION

被引：0
|
作者：
Demario, Caio L. [1 ]
Miranda, Paulo A. V. [1 ]
机构：
[1] Univ Sao Paulo, Inst Math & Stat, BR-05508090 Sao Paulo, SP, Brazil
来源：
2019 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2019年
基金：
巴西圣保罗研究基金会;
关键词：
Relaxed Segmentation; Oriented Image Foresting Transform; Random Walks; CUT;
D O I：
10.1109/icip.2019.8803080
中图分类号：
TB8 [摄影技术];
学科分类号：
0804 ;
摘要：
In this work, we propose a hybrid method for seeded image segmentation, named Relaxed OIFT, which extends a method by Malmberg et al. to directed graphs, to properly incorporate the boundary polarity constraint. Relaxed OIFT, lies between the pure Oriented Image Foresting Transform (OIFT) at one end and the extension of Random Walks (RW) to directed graphs as proposed by Singaraju et al. Relaxed OIFT is evaluated in MR and CT medical images, producing more intuitively correct segmentation results than both OIFT and RW, and being easy to be extended to multi-dimensional images.
引用
收藏
页码：1520 / 1524
页数：5
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