Image processing method for epilating device, apparatus therefor and epilating device

By segmenting pores and recognizing skin color in skin images, generating feature vectors, and using a pre-trained model to output personalized energy parameters, the problem of traditional hair removal devices being unable to adapt to individual skin types is solved, thus improving the reliability and safety of the device.

CN122350863APending Publication Date: 2026-07-10CHONGQING PUMENCHUANG BIOTECHNOLOGY CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CHONGQING PUMENCHUANG BIOTECHNOLOGY CO LTD
Filing Date
2025-12-27
Publication Date
2026-07-10

AI Technical Summary

Technical Problem

Traditional hair removal devices have a single energy regulation method, which cannot adapt to the individual skin differences of different users, resulting in poor hair removal effect or skin burns. In addition, they rely on subjective experience to make judgments, which is prone to errors and have poor reliability.

Method used

By acquiring skin images, performing pore segmentation and skin color recognition, generating feature vectors, and using a pre-trained energy parameter prediction model to output personalized energy parameters, the traditional fixed-level adjustment is replaced.

Benefits of technology

It enables precise energy adjustment based on individual pore condition and skin tone differences, avoiding poor hair removal results and skin burns, and improving the reliability of the device.

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Abstract

This application relates to an image processing method and apparatus for hair removal devices, and the hair removal device itself. The method includes: acquiring a skin image of the skin surface to be treated for hair removal; performing pore segmentation on the skin image to obtain a mask image indicating the segmentation result; determining the pore diameter and pore density of the skin surface based on the mask image; performing skin color recognition on the skin image to determine skin color characterization information of the skin surface; generating a feature vector based on the pore diameter, pore density, and skin color characterization information; and predicting predicted energy parameters based on the feature vector using a pre-trained energy parameter prediction model, wherein the predicted energy parameters are used to control the hair removal process of the hair removal device. This method can improve the reliability of hair removal devices.
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