Understanding the opening fluctuation of glottis is meaningful in diagnosing vocal cord dysfunction. Nasopharyngoscopy can offer a direct method for visualizing the opening and closing of the glottis. However, the large amount of image data presents a significant challenge for quantitative analysis of the video recordings. Thus, automatic image processing method allowing for batch analysis of glottic images becomes clinically important. Here, we present an image processing method using Gaussian smoothing filter and threshold segmentation, followed by differentiation and Canny image edge detection for tracking changes in glottis dimensions (the opening area). A quantitative assessment of true glottic size was also developed for calibration in our study. This method was used to analyze different video data acquired from clinical nasopharyngoscopy of 8 healthy subjects during either normal breathing, breathing with cough or with 'Hee' sound. The results indicated that the computed glottic area change waveform was consistent with the observed glottic fluctuation in the video from nasopharyngoscopy. Thus, our proposed method may provide an accurate and efficient detection of glottic aperture and quick assessment of glottic fluctuations to assist clinical diagnosis of vocal cord dysfunction and other airway pathologies.