Edge Prior Multilayer Segmentation Network Based on Bayesian Framework
Joint Authors
He, Chu
Shi, Zishan
Fang, Peizhang
Xiong, Dehui
He, Bokun
Liao, Mingsheng
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-02-10
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
In recent years, methods based on neural network have achieved excellent performance for image segmentation.
However, segmentation around the edge area is still unsatisfactory when dealing with complex boundaries.
This paper proposes an edge prior semantic segmentation architecture based on Bayesian framework.
The entire framework is composed of three network structures, a likelihood network and an edge prior network at the front, followed by a constraint network.
The likelihood network produces a rough segmentation result, which is later optimized by edge prior information, including the edge map and the edge distance.
For the constraint network, the modified domain transform method is proposed, in which the diffusion direction is revised through the newly defined distance map and some added constraint conditions.
Experiments about the proposed approach and several contrastive methods show that our proposed method had good performance and outperformed FCN in terms of average accuracy for 0.0209 on ESAR data set.
American Psychological Association (APA)
He, Chu& Shi, Zishan& Fang, Peizhang& Xiong, Dehui& He, Bokun& Liao, Mingsheng. 2020. Edge Prior Multilayer Segmentation Network Based on Bayesian Framework. Journal of Sensors،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1190506
Modern Language Association (MLA)
He, Chu…[et al.]. Edge Prior Multilayer Segmentation Network Based on Bayesian Framework. Journal of Sensors No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1190506
American Medical Association (AMA)
He, Chu& Shi, Zishan& Fang, Peizhang& Xiong, Dehui& He, Bokun& Liao, Mingsheng. Edge Prior Multilayer Segmentation Network Based on Bayesian Framework. Journal of Sensors. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1190506
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1190506