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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.