Motion saliency based automatic delineation of glottis contour in high-speed digital images

In recent years, high-speed videoendoscopy (HSV) has significantly aided the diagnosis of voice pathologies and furthered the understanding the voice production in recent years. As the first step of these studies, automatic segmentation of glottal images till presents a major challenge for this technique. In this paper, we propose an improved Saliency Network that automatically delineates the contour of the glottis from HSV image sequences. Our proposed additional saliency measure, Motion Saliency (MS), improves upon the original Saliency Network by using the velocities of defined edges. In our results and analysis, we demonstrate the effectiveness of our approach and discuss its potential applications for computer-aided assessment of voice pathologies and understanding voice production.

• Publication year

  2017

• Venue

  2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)

• Publication date

  2017-04-09

• Fields of study

  Medicine, Computer Science, Engineering

• Identifiers
  DOI 10.1109/ICIEA.2017.8282998arXiv 1704.02567
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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