Automatic Segmentation of High Speed Video Images of Vocal Folds
An automatic method for segmenting glottis in high speed endoscopic video (HSV) images of vocal folds is proposed. The method is based on image histogram modeling. Three fundamental problems in automatic histogram based processing of HSV images, which are automatic localization of vocal folds, defor...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2014/818415 |
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| Summary: | An automatic method for segmenting glottis in high speed endoscopic video
(HSV) images of vocal folds is proposed. The method is based on image
histogram modeling. Three fundamental problems in automatic histogram
based processing of HSV images, which are automatic localization of vocal
folds, deformation of the intensity distribution by nonuniform illumination,
and ambiguous segmentation when glottal gap is small, are addressed. The
problems are solved by using novel masking, illumination, and reflectance
modeling methods. The overall algorithm has three stages: masking, illumination
modeling, and segmentation. Firstly, a mask is determined based on
total variation norm for the region of interest in HSV images. Secondly, a
planar illumination model is estimated from consecutive HSV images and reflectance
image is obtained. Reflectance images of the masked HSV are used
to form a vertical slice image whose reflectance distribution is modeled by a
Gaussian mixture model (GMM). Finally, estimated GMM is used to isolate
the glottis from the background. Results show that proposed method provides
about 94% improvements with respect to manually segmented data in
contrast to conventional method which uses Rayleigh intensity distribution
in extracting the glottal areas. |
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| ISSN: | 1110-757X 1687-0042 |