Acoustic Based Method for Automatic Segmentation of Images of Objects in Periodic Motion: detection of vocal folds edges case study

Abstract

We describe a novel image segmentation technique for automated detection of objects being in periodic motion that generates acoustic waves. The method is based on measuring similarity of two independently collected but time synchronized data, i.e. the audio signals and image sequences. Such a technique enables automatic and optimized segmentation procedure of a sequence of images depicting an oscillating object. The proposed segmentation procedure has been validated on the problem of detecting edges of vibrating vocal folds. The similarity measure of the synchronously collected sequence of laryngoscopic images and the voice signal is achieved by applying time-frequency analysis. The developed segmentation technique and motion analysis method can be applied for early detection of oscillation anomalies of the vocal folds which may cause hoarse voice, also known as dysphonia. In particular, the image segmentation result can aid the phoniatrist in the analysis of the vocal folds phonation process and help in early detection of voice anomalies.