Intelligent face skin aging degree identification and evaluation method

Abstract

The invention discloses an intelligent face skin aging identification and evaluation method. The method comprises the steps of image collection and preprocessing, namely collecting a face image used for assessing the aging degree of the face skin, converting the image into a grayscale image from an RGB image, carrying out Gaussian convolution on the grayscale image, and carrying out Hessian matrixalgorithm calculation to obtain a binary image; wrinkle detection and screening, namely judging whether the region with the value of 1 in the binary image is a suspected wrinkle region, judging whether the suspected wrinkle region is a real wrinkle or not according to the minimum bounding rectangle of the region and the inclination angles of the long edge, the short edge and the long edge of theregion, and processing to obtain a new wrinkle binary image; extraction of wrinkle features. Wherein the region with the value of 1 in the wrinkle binary image is a real wrinkle region, and extractinghuman face wrinkle characteristics including the number of wrinkles, the maximum communicating length of the wrinkles, the maximum width, the wrinkle color depth degree and the minimum circumscribedrectangular area of the wrinkles; evaluation of human face skin aging degree. And the human face skin aging degree and the human face skin visual aging degree are obtained through weighted comprehensive calculation of the human face wrinkle characteristics. According to the method, the human face skin aging degree is comprehensively judged by rapidly and accurately detecting the human face wrinkleindex, and the quantitative index is provided.

Description

technical field [0001] The invention relates to the field of image processing, in particular to an image processing method for identifying and evaluating the aging degree of human face skin. Background technique [0002] With the continuous development of the beauty and skin care industry, people pay more and more attention to skin quality. How to detect and quantify the aging skin indicators of the face has become a key technology. At present, most of the domestic evaluations of the aging degree of human face skin are based on the competent evaluation of clinicians rather than the objective evaluation of computer vision. They mainly focus on evaluating the severity of wrinkles, and cannot accurately locate facial wrinkles and provide quantitative indicators. In view of the above problems, it is very necessary to design a method that can quickly and accurately detect human facial skin wrinkles and provide quantitative indicators of aging degree for its analysis. [0003] In...

AI Technical Summary

Problems solved by technology

This method provides a wrinkle detection method based on deep learning in the cloud, but the method adopted is the photometric stereo method, which has high environmental requirements and poor applicability

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