Dynamic self-adaption skin color segmentation method and device

Abstract

The invention provides a dynamic self-adaption skin color segmentation method and a device. The method comprises the following steps: a red green blue (RGB) image is obtained; colors and space of the RGB image are transformed to obtain a hue saturation value (HSV) image; a face of a person is tested to obtain a position and an area of the face; color values of a skin color pixels in the face area are collected to serve as a skin color sample, and color values of positions with intense light changes are recorded to serve as a skin color change sample; each chromatic value or saturation value of histograms of the skin color sample and the skin color change sample are polled and are combined with predetermined weight; through the covering rate of the pixel counts within the chrominance or saturation threshold ranges of the histograms to the total counts of the corresponding histograms, skin color segmentation threshold values are obtained; the skin colors are tested through the skin color segmentation threshold values. By means of the above method and device, the skin color dynamic and self-adaption segmentation can be achieved, and thereby the accuracy of the skin color testing and the adaptability of the skin color testing to light changes are improved.

Description

technical field [0001] Embodiments of the present invention relate to the field of image processing, and more specifically, to a method and device for dynamic adaptive skin color segmentation. Background technique [0002] Skin color segmentation is an important content in machine vision at present. In the fields of face detection, gesture recognition, and yellow information video detection, skin color segmentation plays a key role. [0003] The basis of the skin color segmentation technology is based on the clustering characteristics of skin color. Although the skin tones of different people have some differences in brightness, but in terms of chroma and saturation, the skin tones will be gathered in a range, and then according to this range, skin tones and non-skin tones can be distinguished. In the existing skin color segmentation methods, the RGB color space is converted into the YCbCr color space or the HSV color space, and then in the converted space, the skin color s...

AI Technical Summary

Problems solved by technology

[0008] However, the above dynamic skin color segmentation methods are still low in the accuracy of skin color detection and are greatly affected by illumination changes.

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