Face detection method based on Gaussian model and minimum mean-square deviation

Abstract

The invention provides a face detection method based on a Gaussian model and a minimum mean-square deviation, and relates to a face recognition technology. A face detection method based on the Gaussian model and the minimum mean-square deviation under the premise of a complicated background, a side face, a stopper and a plurality of faces. The method comprises the following steps of: building a YCbCr Gaussian model: building the YCbCr Gaussian model for face skin color distribution according to collected skin color sample data, and performing lighting compensation on the image, wherein in the YCbCr, Y is a brightness component, Cb is a blue chroma component, and Cr is a red chroma; performing skin color segmentation on the image by using the built YCbCr Gaussian model and the minimum mean-square deviation; performing binaryzation on a skin color region, and processing a binary image by opening to eliminate a small bridge and discrete points; rejecting detected non-face regions in the similar skin color or skin color according to future knowledge of a face; and finally marking a face position by using a rectangular frame.

Description

Face detection method based on Gaussian model and minimum mean square error technical field The invention relates to a face recognition technology, in particular to a rapid face detection method in a color image under complex backgrounds, sides, occluders and multiple faces. Background technique Face detection means that for any given image, a certain strategy is used to search it to determine whether there is a human face in it, and if there is, further determine the position, size and posture of the human face. With the enhancement of e-commerce and people's safety awareness, people have higher requirements for confirming personal identity, and the technology of using biometrics to identify personal identity has also been given high expectations. Face recognition technology is easier to be accepted by people than fingerprint iris, and has become the most potential biometric authentication method to be tested. At present, face detection is widely used in video conferenci...

AI Technical Summary

Problems solved by technology

The purpose of the present invention is to provide a kind of face detection based on Gaussian model and minimum mean square error in complex background, side, occluder, multi-face situation for the defects existing in the existing algorithm and the difficulty of face detection method

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