An automated glottal image analysis system capable of processing ultra high-speed laryngeal films successively has been developed.
The objective of this ultra high-speed laryngeal film is to obtain a permanent record of vocal cord motion during phonation. These films are then analyzed frame-by-frame for data relevant to the theory of vocal cord motion and to the detection of laryngeal pathologies. Because of the massive amount of data, several automated systems have been developed to extract such parameters as glottal area, length, width, etc.
The system that has been developed detects the glottal boundary from the glottal image, and describes its shape by angular bend function. And it measures glottal area and width for the glottal waveform. Using the data of glottal shape and glottal waveform, estimations of the vocal cord vibration patterns are attempted. Some parameters are defined ; as “Difference Factor (D)”, “Complexity Factor (F)”, and “Symmetry Factor (S)”. Parameter D is to measure the difference between two glottal boundary shapes. Parameter F is to measure the complexity and width of glottal patterns. And parameter S is to measure the symmetry of vocal cord vibration patterns. By using these parameters, vocal cord vibration patterns can be estimated quantitatively.
In this paper, we analyzed the images of extracted larynx of a dog under several conditions ; such as the control case, additional weight loaded case, silicon injected case, operated case, and the over-operated case. As a result, each condition has been classified clearly, and successful observation of the glottal wave and detection of laryngeal pathologies have been made possible.
