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Journal of Applied Mathematics
Volume 2014, Article ID 818415, 16 pages
Research Article

Automatic Segmentation of High Speed Video Images of Vocal Folds

1Department of Electronic Communication Engineering, Süleyman Demirel University, 03200 Isparta, Turkey
2Department of Electrical and Electronics Engineering, Middle East Technical University, 06800 Ankara, Turkey

Received 24 January 2014; Revised 18 April 2014; Accepted 20 April 2014; Published 5 June 2014

Academic Editor: Feng Gao

Copyright © 2014 Turgay Koç and Tolga Çiloğlu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.