High-precision face recognition method and face recognition equipment
A face recognition, high-precision technology, applied in the field of face recognition, can solve problems such as unfavorable action deployment, recognition errors, and inaccuracy of face recognition.
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Embodiment 1
[0091] This embodiment provides a high-precision face recognition method, such as figure 1 shown, including:
[0092] Step 1: collect target images based on the camera, and read the target images, determine the face range in the target image, and delineate the face range to output a face image;
[0093] Step 2: Determine the face recognition model, and input the face image into the face recognition model for face recognition, and output the recognition result;
[0094] Step 3: Match the recognition result in the preset identity database to determine the identity information of the face.
[0095] In this embodiment, the target image may be an image acquired based on the shooting range of the camera.
[0096] In this embodiment, the face recognition model may be a face recognition model obtained by extracting face samples for training.
[0097] In this embodiment, the preset identity database may be set in advance, and is equipped with all identity databases that have recorde...
Embodiment 2
[0101] On the basis of Embodiment 1, this embodiment provides a high-precision face recognition method, which is characterized in that, as figure 2 As shown, in the step 1, the specific working process of reading the target image and determining the face range in the target image includes:
[0102] Step 101: Perform grayscale processing on the target image, acquire a grayscale image, and read the grayscale image to determine the pixels of the grayscale image;
[0103] Step 102: extracting the features of the pixels of the grayscale image, and determining the distribution characteristics of pixels of the same type of features in the grayscale image;
[0104] Step 103: Compare the target image with the grayscale image, and determine the contour range of the face in the grayscale image based on the distribution characteristics of pixels of the same type of feature in the grayscale image, and determine Face contour pixels;
[0105] Step 104: Mark the face contour pixels, and de...
Embodiment 3
[0111] On the basis of Embodiment 1, this embodiment provides a high-precision face recognition method. In step 1, the specific working process of delineating the range of the human face and outputting the facial image of the human face includes:
[0112] Acquiring edge point information of the human face range, and determining the sharpening degree of the boundary of the human face range based on the edge point information of the human face range;
[0113] performing edge sharpening on the boundary of the face range according to the sharpening degree, and inputting the target image after edge sharpening of the face range into a preset segmentation model;
[0114] determining the segmentation point of the target image in the preset segmentation model, and segmenting the target image in the preset segmentation model based on the segmentation point;
[0115] The facial image of the human face is generated based on the segmentation result.
[0116] In this embodiment, the edge p...
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