TITLE:
A Restricted, Adaptive Threshold Segmentation Approach for Processing High-Speed Image Sequences of the Glottis
AUTHORS:
Mathew Blanco, Xin Chen, Yuling Yan
KEYWORDS:
Segmentation; Glottis; Vocal Fold Motion; Difference Image; Adaptive Threshold
JOURNAL NAME:
Engineering,
Vol.5 No.10B,
November
1,
2013
ABSTRACT:
In this paper, we propose a restricted, adaptive
threshold approach for the segmentation of images of the glottis acquired from
high speed video-endoscopy (HSV). The approach involves first, identifying a region
of interest (ROI) that encloses the vocal-fold motion extent for each image
frame as estimated by the different image sequences. This procedure is then
followed by threshold segmentation restricted within the identified ROI for
each image frame of the original image sequences, or referred to as sub-image
sequences. The threshold value is adapted for each sub-image frame and
determined by respective minimum gray-scale value that typically corresponds to
a spatial location within the glottis. The proposed approach is practical and
highly efficient for segmenting a vast amount of image frames since simple
threshold method is adapted. Results obtained from the segmentation of
representative clinical image sequences are presented to verify the proposed
method.