Automatic Segmentation of Glottal Space from Video Images Based on Mathematical Morphology and the hough Transform

Davod Aghlmandi, Karim Faez


Vocal disorders directly arise from the physical shape of the vocal cords. Videostroboscopic imaging provides doctors with valuable information about the physical shape of the vocal cords and about the way these cords move. Segmentation of the glottal space is necessary in order to characterize morphological disorders of vocal folds. One of the main problems with the methods presented is their low level of accuracy. To solve this problem, an automatic method based on Mathematical Morphology edge detection and the Hough transformation is presented in this article to extract the glottal space from the videostroboscopic images presented. Our method compared with the histogram and active contours methods and the findings showed that our proposed method yields better results.


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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578