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 :
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