A Spatially Correlated Mixture Model for Image Segmentation

URI http://harp.lib.hiroshima-u.ac.jp/hiroshima-cu/metadata/12388
File
Title
A Spatially Correlated Mixture Model for Image Segmentation
Author
氏名 KURISU Kosei
ヨミ クリス コウセイ
別名 栗栖 昂勢
氏名 SUEMATSU Nobuo
ヨミ スエマツ ノブオ
別名 末松 伸朗
氏名 IWATA Kazunori
ヨミ イワタ カズノリ
別名 岩田 一貴
氏名 HAYASHI Akira
ヨミ ハヤシ アキラ
別名 林 朗
Subject
image segmentation
Gaussian processes
mixture models
Abstract

In image segmentation, finite mixture modeling has been widely used. In its simplest form, the spatial correlation among neighboring pixels is not taken into account, and its segmentation results can be largely deteriorated by noise in images. We propose a spatially correlated mixture model in which the mixing proportions of finite mixture models are governed by a set of underlying functions defined on the image space. The spatial correlation among pixels is introduced by putting a Gaussian process prior on the underlying functions. We can set the spatial correlation rather directly and flexibly by choosing the covariance function of the Gaussian process prior. The effectiveness of our model is demonstrated by experiments with synthetic and real images.

Description Peer Reviewed
Journal Title
IEICE Transactions on Information and Systems
Volume
E98-D
Issue
4
Spage
930
Epage
937
Published Date
2015-4-1
Publisher
社団法人電子情報通信学会
ISSN
09168532
NCID
AA10826272
AA11226532
DOI
10.1587/transinf.2014EDP7307
NAID
130005061856
Language
jpn
NIIType
Journal Article
Text Version
出版社版
Rights
Copyright © 2015 The Institute of Electronics, Information and Communication Engineers
Relation URL
Old URI
Set
hiroshima-cu