Automatic segmentation of color lip images based on morphological filter

Meng Li*, Yiu Ming CHEUNG

*Corresponding author for this work

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

6 Citations (Scopus)

Abstract

This paper addresses the problem of lip segmentation in color space, which is a crucial issue to the success of a lip-reading system. We present a new segmentation approach to lip contour extraction by taking account of the color difference between lip and skin in color space. Firstly, we obtain a lip segment sample via a color transformation sequence in 1976 CIELAB and LUX color spaces. Secondly, we establish a Gaussian model and make use of the hue and saturation value of each pixel within the lip segment to estimate the model parameters. Subsequently, the memberships of lip and non-lip regions are calculated, respectively. Thirdly, we employ morphological filters to obtain the desirable lip region approximately based on the memberships. Finally, we extract the lip contour via convex hull algorithm with the prior knowledge of the human mouth shape. Experiments show the efficacy of the proposed approach in comparison with the existing lip segmentation methods.

Original languageEnglish
Title of host publicationArtificial Neural Networks, ICANN 2010 - 20th International Conference, Proceedings
Pages384-387
Number of pages4
EditionPART 1
DOIs
Publication statusPublished - 2010
Event20th International Conference on Artificial Neural Networks, ICANN 2010 - Thessaloniki, Greece
Duration: 15 Sep 201018 Sep 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume6352 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Artificial Neural Networks, ICANN 2010
Country/TerritoryGreece
CityThessaloniki
Period15/09/1018/09/10

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

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