Method for automatically identifying facial skin wrinkles and automatically grading wrinkle severity

A skin wrinkle and automatic identification technology, applied in the field of biostatistics, can solve the problems of inaccurate and unrealistic evaluation of wrinkle severity, and achieve the effect of convenient and fast skin wrinkle grading analysis

Pending Publication Date: 2019-08-09
深圳市华嘉生物智能科技有限公司
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Problems solved by technology

However, due to the influence of subjective emotions and limitations of professional knowledge, the evaluation of the severity of wrinkles by ordinary people is often not accurate enough; the evaluation of professional doctors is often more reasonable, but limited by environmental factors such as time and place, it is not reasonable to invite professional doctors to make a judgment. feasible

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  • Method for automatically identifying facial skin wrinkles and automatically grading wrinkle severity
  • Method for automatically identifying facial skin wrinkles and automatically grading wrinkle severity
  • Method for automatically identifying facial skin wrinkles and automatically grading wrinkle severity

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Embodiment Construction

[0055] Conditions for capturing and accepting facial skin images:

[0056] In the present invention, the human face and skin images used in the experiment are obtained by taking pictures with a VISIA skin detector, but the method proposed by the present invention is also applicable to the human face and skin images collected by other digital cameras or optical instruments. The face image should be clear, with good lighting, and no shadows or hair covering the bags under the eyes, eye corners, and forehead wrinkles. In addition, the image should not be processed by filters or PS.

[0057] Face image recognition and face feature point classification:

[0058] In the present invention, use the dlib toolkit (Python call) to detect and identify the face image, and obtain a collection that includes 68 face feature points simultaneously, and divide the face feature points in the following manner:

[0059] The 0-16 feature points in the feature point set are the face contour feature ...

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Abstract

The invention discloses a method for automatically identifying human face skin wrinkles and automatically grading wrinkle severity. The invention relates to the field of computer vision of artificialintelligence, based on a clear face photo, a method of face recognition, image segmentation, wrinkle recognition, feature extraction and prediction grading can be sequentially adopted to automaticallyrecognize wrinkles in a face skin image and automatically grade the severity, and the accuracy of automatic grading can reach 0.85. The method is fully automatically and quickly realized through a computer, has the accuracy of wrinkle assessment by professionals, can be widely applied to industries such as medical beauty, cosmetics and the like, and can also assist in research related to skin wrinkles.

Description

technical field [0001] The method adopted in the invention relates to face recognition, image segmentation, wrinkle recognition, feature extraction and wrinkle automatic classification, and relates to the fields of computer vision and biostatistics of artificial intelligence. Background technique [0002] Human beings can automatically find wrinkled areas in human faces or human face images with the naked eye, and make subjective evaluations of the severity of observed wrinkles. However, due to the influence of subjective emotions and limitations of professional knowledge, the evaluation of the severity of wrinkles by ordinary people is often not accurate enough; the evaluation of professional doctors is often more reasonable, but limited by environmental factors such as time and place, it is not reasonable to invite professional doctors to make a judgment. Reality works. Therefore, there is an urgent need for a convenient and accurate automatic assessment method of wrinkle...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06T7/11
CPCG06T7/11G06T2207/10004G06V40/161G06V40/165G06V40/168G06V40/172
Inventor 李嘉路华芮李骁张游龙王润苗
Owner 深圳市华嘉生物智能科技有限公司
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