liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Lip segmentation based on Lambertian shadings and morphological operators for hyper-spectral images
CNR, Italy.
CNR, Italy.
Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-6385-6760
Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, Faculty of Science & Engineering.
Show others and affiliations
2017 (English)In: Pattern Recognition, ISSN 0031-3203, E-ISSN 1873-5142, Vol. 63, p. 355-370Article in journal (Refereed) Published
Abstract [en]

Lip segmentation is a non-trivial task because the colour difference between the lip and the skin regions maybe not so noticeable sometimes. We propose an automatic lip segmentation technique for hyper-spectral images from an imaging prototype with medical applications. Contrarily to many other existing lip segmentation methods, we do not use colour space transformations to localise the lip area. As input image, we use for the first time a parametric blood concentration map computed by using narrow spectral bands. Our method mainly consists of three phases: (i) for each subject generate a subset of face images enhanced by different simulated Lambertian illuminations, then (ii) perform lip segmentation on each enhanced image by using constrained morphological operations, and finally (iii) extract features from Fourier-based modeled lip boundaries for selecting the lip candidate. Experiments for testing our approach are performed under controlled conditions on volunteers and on a public hyper-spectral dataset. Results show the effectiveness of the algorithm against low spectral range, moustache, and noise.

Place, publisher, year, edition, pages
ELSEVIER SCI LTD , 2017. Vol. 63, p. 355-370
Keywords [en]
Lip spatial pattern; Segmentation; Blood concentration map; Hyper-spectral; Lambertian shading; Morphological; Fourier descriptors
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:liu:diva-133720DOI: 10.1016/j.patcog.2016.10.007ISI: 000389785900028OAI: oai:DiVA.org:liu-133720DiVA, id: diva2:1063928
Note

Funding Agencies|European Commission [611516]

Available from: 2017-01-11 Created: 2017-01-09 Last updated: 2017-11-29

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Search in DiVA

By author/editor
Larsson, MarcusStrömberg, Tomas
By organisation
Biomedical InstrumentationFaculty of Science & Engineering
In the same journal
Pattern Recognition
Medical Image Processing

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 139 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf