Map-MRF based LIP segmentation without true segment number

Yiu Ming CHEUNG*, Meng Li

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

This paper presents an MAP-MRF (i.e. maximum a posteriori - Markov random field) based image segmentation method to achieve stable performance without knowing the true segment number in advance. Specifically, we firstly assign the segment number a value greater than or equal to the ground truth. Subsequently, cluster centroid of each segment in observation space is initialized randomly so that each pixel can be assigned the Euclidean distance-based membership. Then, a 2-D MRF is constructed on the regular pixel lattice of the interesting image. Under MAP-MRF framework, the image segmentation can be regarded as a labeling problem with the label configuration determined by the segment label of membership winner on each site. We therefore propose an iterative algorithm by optimizing the objective function to fade out the over-segmentation, through which an optimal segmentation is achieved. Finally, an unsupervised lip segmentation scheme based on the proposed method is presented. Experiment shows its outstanding performance.

Original languageEnglish
Title of host publicationICIP 2011
Subtitle of host publication2011 18th IEEE International Conference on Image Processing
Pages769-772
Number of pages4
DOIs
Publication statusPublished - 2011
Event2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium
Duration: 11 Sep 201114 Sep 2011

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference2011 18th IEEE International Conference on Image Processing, ICIP 2011
Country/TerritoryBelgium
CityBrussels
Period11/09/1114/09/11

Scopus Subject Areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

User-Defined Keywords

  • Image segmentation
  • MAP-MRF framework
  • segment number

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