Self-adapting face identification method and device
A face recognition and self-adaptive technology, which is applied in the field of face recognition and biometrics recognition, can solve the problems such as the decline of user recognition pass rate and slow recognition speed, so as to improve the recognition accuracy, increase the recognition speed, and reduce the difficulty of recognition Effect
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Embodiment 1
[0035] Such as figure 1 Shown, a kind of adaptive face recognition method, this method comprises the following steps:
[0036] Step S101: Enter the basic information of the face user, collect a plurality of face images of the face user, and extract face features from them as face feature templates, and save the basic face user information and face feature templates to Face user information database;
[0037] Specifically, input the basic information such as the number, name, address, and contact information of the face user for user retrieval or voice broadcast or display after user identification is successful; continuously collect the face images of the registered users, and each user needs to Collect multiple face images from different angles; for each face image collected, use the Garbor wavelet feature method and the local binary pattern (LBP, local Binary Patterns) method to extract a set of face features F m , and respectively calculate the facial features and the ext...
Embodiment 2
[0050] Such as figure 2 Shown, a kind of adaptive face recognition method, this method comprises the following steps:
[0051] Step S201: Enter the basic information of the face user, collect a plurality of face images of the face user, and extract face features from them as face feature templates, and save the basic information of the face user and the face feature template to Face user information database.
[0052] Specifically input the basic information such as the number, name, address, and contact information of the face user, which is used for user retrieval or voice broadcast or display after the user identification is successful; continuously collect the face images of the registered users, and each user needs to collect Multiple face images from different angles; each face image is collected, using the Garbor wavelet feature method and the LBP (local Binary Patterns) method to extract a set of face features F m , and respectively calculate the facial features and...
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