Human face recognition method
A face recognition and face image technology, applied in the field of face recognition research, can solve problems such as not being ideal, face recognition system is not suitable, a large number of training images, etc., to achieve good robustness, high practical value, and complex algorithms low degree of effect
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[0034] Example 1
[0035] see figure 1 , In this embodiment, for the influence of illumination changes on face recognition, the classical illumination invariant feature representation algorithm is studied, and a face recognition method based on illumination invariant features is proposed. The method includes the steps:
[0036] 1) First use Gaussian filter to filter out the noise in the original image.
[0037] 2) A data set is established for each pixel of the face image, and the data set is composed of the gray value of the pixel and the gray values of its adjacent 8 pixels.
[0038] 3) Using the gray value of 8 adjacent pixels combined with the maximum likelihood estimation method to estimate the standard deviation parameter in the Gaussian density function with the gray value of the pixel as the mean value.
[0039] 4) Calculate the ratio of the estimated value of the standard deviation to the gray value of the pixel, and use the arc tangent function to compare the val...
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