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Assessment of the Mouth

Assessment of the Mouth

A thorough mouth assessment, including inspection and palpation of the lips, gums, tongue, tonsils, uvula, and pharynx, is crucial in detecting potential health issues. Diseases ranging from oral cancer to systemic conditions like diabetes could be identified early through careful oral examination. This article provides a detailed guide on conducting a comprehensive mouth assessment.
Mouth Inspection
The inspection begins with visually examining the mouth for symmetry, color, and size.

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Related Experiment Video

Updated: Oct 4, 2025

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

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Published on: April 14, 2023

Collaborative Research on Mouth Shape and Lyrics in Singing Practice Based on Image Processing.

Lujia Xu¹, Chen Chen²

¹Xiamen University Tan Kah Kee College, Zhangzhou 363123, China.

Computational Intelligence and Neuroscience

|February 7, 2022

Summary

This study introduces an image processing technique for synchronizing singing video subtitles with lip movements. The developed lip-reading recognition system significantly improves accuracy and user experience.

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Area of Science:

Computer Vision
Digital Signal Processing
Human-Computer Interaction

Background:

Subtitle and lip-sync discrepancies in singing videos degrade the viewer experience.
Manual correction is labor-intensive and costly.

Purpose of the Study:

To develop an automated image processing system for lip-reading recognition.
To synchronize singing video subtitles with the singer's lip movements.
To enhance the audio-visual experience for viewers.

Main Methods:

Utilized image processing for lip-reading recognition.
Implemented a system to extract lip-reading data and correct mouth shapes and subtitles.
Employed cascade lip region feature extraction methods, comparing them against DCT and DWT.
Optimized mouth shape classification and image correction.

Main Results:

Achieved an average frame processing time of 628 ms with a 98.80% success rate.
Demonstrated reliable identification of portrait and lip areas from various angles.
Cascade feature extraction improved recognition rates by nearly 10% and reduced feature vector dimensions by 65% compared to DCT and DWT.
Mouth shape and subtitle correction achieved a success rate exceeding 90%.

Conclusions:

The developed image processing system effectively synchronizes subtitles with lip movements in singing videos.
The lip-reading recognition technology offers significant improvements in accuracy and efficiency.
The system provides a superior audio-visual interactive experience and has potential for further optimization.