DocumentCode
2175730
Title
Parametric Control in a Region-Based Coupled MRF Model with Phase Dynamics for Coarse Image Region Segmentation
Author
Liang, Haichao ; Nakada, Kazuki ; Matsuzaka, Kenji ; Morie, Takashi ; Okada, Masato
Author_Institution
Grad. Sch. of Life Sci. & Syst. Eng., Kyushu Inst. of Technol., Kitakyushu, Japan
fYear
2010
fDate
11-13 Dec. 2010
Firstpage
190
Lastpage
195
Abstract
Towards hardware implementation of real-time visual image processing, we propose a piecewise linear (PWL) approximation of a coupled region-based Markov Random Field (MRF) model with hidden phase variables for coarse image region segmentation. We introduce PWL functions into update equations of the region-based model, in order to make it easy to control parameters that determine the balance between image segmentation and smoothing, as well as to make it efficient for hardware implementation. We can tune filtering properties of our model by controlling the parameters of the PWL functions in applications to a task of coarse image region segmentation. Finally, we demonstrate that closed regions in input images can be represented by phase variables in multi-scale.
Keywords
image segmentation; piecewise linear techniques; Markov random field model; image region segmentation; parametric control; phase dynamic; piecewise linear approximation; real time visual image processing; region based coupled MRF model; Computational modeling; Cost function; Fuses; Image segmentation; Mathematical model; Smoothing methods; boundary-based; coarse image region segmentation; parametric control; piecewise linear functions; region-based coupled MRF models;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Science and Engineering (CSE), 2010 IEEE 13th International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-9591-7
Electronic_ISBN
978-0-7695-4323-9
Type
conf
DOI
10.1109/CSE.2010.32
Filename
5692474
Link To Document