Paper Info
Title
Lip segmentation based on Lambertian shadings and morphological operators for hyper-spectral images.
Abstract
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.
Year
DOI
Venue
2017
10.1016/j.patcog.2016.10.007
Pattern Recognition
Keywords
Field
DocType
Lip spatial pattern,Segmentation,Blood concentration map,Hyper-spectral,Lambertian shading,Morphological,Fourier descriptors
Computer vision,Scale-space segmentation,Moustache,Pattern recognition,Segmentation,Fourier transform,Parametric statistics,Operator (computer programming),SKIN REGIONS,Artificial intelligence,Spectral bands,Mathematics
Journal
Volume
Issue
ISSN
63
C
0031-3203
Citations 
PageRank 
References 
2
0.38
20
Authors
6
Name
Order
Citations
PageRank
Alessandro Danielis120.38
D. Giorgi244425.62
Marcus Larsson351.53
Tomas Strömberg451.53
Sara Colantonio55814.24
Ovidio Salvetti616846.26