A low-resolution face recognition method
A face recognition, low-resolution technology, applied in the field of biometrics, can solve problems such as unsatisfactory face recognition, achieve the effect of improving recognition performance, strengthening classification ability, and perfect extraction
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[0054] The principles and features of the present invention will be described below with reference to the accompanying drawings. The examples cited are only used to explain the present invention and not used to limit the scope of the present invention.
[0055] Such as figure 1 As shown, a face recognition method under low resolution conditions includes the following steps:
[0056] S1. Obtain a low-resolution face image sample as a test sample;
[0057] S2. Extract block LTP and amplitude features from training samples in the face image sample library;
[0058] S3. Perform PCA dimensionality reduction on the block LTP and amplitude characteristics of the training samples;
[0059] S4. Train a KNN classifier through the training samples after dimensionality reduction, and classify the test samples through the KNN classifier to obtain a face recognition result.
[0060] Such as figure 2 As shown, the specific steps of step S2 are:
[0061] S21. Calculate the LTP local domain relationship...
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