A tongue feature intelligent recognition method and system

By processing the tongue surface fluorescence signal using fast Fourier transform and adaptive filtering algorithms, the problems of ambient light interference and changes in tongue image background fluorescence are solved, achieving high accuracy and reliability in detecting tongue image features.

CN121073933BActive Publication Date: 2026-05-29CHAODA CLOUD CLINIC (GUANGDONG) DIGITAL TECHNOLOGY CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
CHAODA CLOUD CLINIC (GUANGDONG) DIGITAL TECHNOLOGY CO LTD
Filing Date
2025-08-22
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Existing technologies struggle to effectively filter out ambient light interference and correct for changes in tongue background fluorescence caused by displacement during tongue surface fluorescence signal acquisition, leading to a decrease in the accuracy and reliability of detection results.

Method used

Fast Fourier Transform (FFT) is used to analyze and identify ambient light digital signals, and digital notch filters are used to remove interference. An adaptive filtering algorithm is then used to correct changes in tongue image background fluorescence, ensuring signal purity and accuracy.

Benefits of technology

It improves the accuracy and reliability of tongue feature identification, reduces the complexity and time cost of the detection process, and enhances the overall efficiency and user experience of the system.

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Abstract

The application provides a tongue feature intelligent recognition method and system, relates to the technical field of biomedical detection, and is characterized in that after obtaining a preprocessed original composite light signal, fixed-frequency environmental light interference is accurately identified and removed through fast Fourier transform analysis, and confusion of environmental noise on subsequent signal processing is avoided.When the target tongue surface area is displaced to cause dynamic changes of background fluorescence signals, a preset adaptive filtering algorithm can accurately identify and remove the changed tongue image background fluorescence digital signal values in real time.This step-by-step and adaptive processing strategy ensures that the removal of environmental light interference and the correction of background fluorescence signals are independent and do not interfere with each other, thereby avoiding the generation of internal processing conflicts and calculation artifacts described in the background technology, and obtaining highly pure and accurate tongue image fluorescence digital signals, significantly improving the accuracy and reliability of tongue feature recognition, and providing a more reliable data basis for oral health detection.
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