Image processing method and mobile terminal
A mobile terminal and image processing technology, applied in the field of image processing, can solve the problems of time-consuming and difficult to meet the user's makeup needs, and achieve the effect of meeting the makeup needs.
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no. 1 example
[0030] refer to figure 1 , showing a flowchart of an image processing method according to an embodiment of the present invention, which is applied to a mobile terminal, and the method may specifically include the following steps:
[0031] Step 101, identifying the face type and facial features type of the face in the target image;
[0032] Among them, the face type includes but not limited to round face, heart-shaped face, melon-shaped face, diamond-shaped face, Chinese-character face and other face types.
[0033] The five sense organs include eyes, eyebrows, nose, ears and mouth. Therefore, the five senses type here means the type of each organ in the above five senses. For example, the type of eyes can include but not limited to big eyes with double eyelids, small eyes with double eyelids, phoenix eyes, single eyelids, etc.; the type of nose can include but not limited to high nose bridge and big nose wings, flat nose bridge and small nose wings, high nose bridge and smal...
no. 2 example
[0072] On the basis of the first embodiment, when step 101 is executed, the figure 2 shown in the method to achieve:
[0073] Step 201, performing face feature recognition on the two-dimensional RGB image, and determining a plurality of feature points;
[0074] Among them, the facial features in the two-dimensional RGB image can be detected, so as to determine various facial feature points in the image. For example, the feature points of facial features and face shape.
[0075] Wherein, the mobile terminal may have a 3D camera, and the method of the embodiment of the present invention may firstly control the 3D camera to take pictures of the user's face, so as to obtain a three-dimensional image, that is, a target image.
[0076] Of course, if the camera is a 2D camera and the target image is a two-dimensional RGB image, then a depth image corresponding to the two-dimensional RGB image and a three-dimensional point cloud image corresponding to the two-dimensional RGB image ...
no. 3 example
[0130] refer to image 3A flow chart showing an image processing method according to another embodiment of the present invention may specifically include the following steps:
[0131] Step 301: Carry out machine learning on the makeup selected by the user on the captured face image, and generate a first correspondence between the user and the type of makeup he likes, and a second correspondence between the user and the facial features;
[0132] Wherein, after the user uses the method of the embodiment of the present invention for multiple times to process the makeup and photographing of the face image, the method of the embodiment of the present invention can record and learn the makeup looks selected by the user each time, so as to determine the makeup that the user likes to use. Makeup type, generate the first corresponding relationship between the user and the favorite type of makeup.
[0133] In addition, in the embodiment of the present invention, the identity of the use...
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