Color Texture Analysis of Moving Vocal Cords Using Approaches from Statistics and Signal Theory

  • Textural features are applied for detection of morphological pathologies of vocal cords. Cooccurrence matrices as statistical features are presented as well as filter bank analysis by Gabor filters. Both methods are extended to handle color images. Their robustness against camera movement and vibration of vocal cords is evaluated. Classification results due to three in vivo sequences are in between 94.4 % and 98.9%. The classification errors decrease if color features are used instead of grayscale features for both statistical and Fourier features

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Author:Christoph PalmORCiDGND, Thomas M. Lehmann, Klaus Spitzer
Parent Title (English):Advances in Quantitative Laryngoscopy, Voice and Speech Research, Procs. 4th International Workshop, Friedrich Schiller University, Jena
Document Type:conference proceeding (article)
Year of first Publication:2000
Release Date:2020/05/18
Tag:Cooccurrence Matrix
Color Texture; Gabor Filter; Image Processing
First Page:49
Last Page:56
Institutes:Fakult├Ąt Informatik und Mathematik
Fakult├Ąt Informatik und Mathematik / Regensburg Medical Image Computing (ReMIC)
Publication:Externe Publikationen
research focus:Digitalisierung