Non-contact heart rate measurement method and system based on face video image
A video image, non-contact technology, applied in the measurement of pulse rate/heart rate, character and pattern recognition, instruments, etc., can solve the problems of measurement stability, different regions, and the accuracy of measurement, so as to achieve convenient measurement, Avoid the effect of affecting
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Embodiment 1
[0038] Such as figure 1 As shown, a non-contact heart rate measurement method based on face video images includes the following steps:
[0039] S101: Acquire multiple frames of RGB images;
[0040] In practical applications, the acquisition of multiple frames of RGB images specifically includes: turning on the camera, and extracting the RGB images from the acquired video.
[0041] In practical applications, the frame rate of the camera is usually set at 10 to 60 frames per second, and the embodiment of the present invention takes 30 frames per second as an example.
[0042]S102: Search the face area of the RGB image in a single frame and determine the cheek center area as the face area of interest ROI1, and perform spatial pixel averaging on the green channel of ROI1 to obtain the average value s1 i ;
[0043] In practical applications, the face area of the RGB image is searched in combination with the Adaboost algorithm and the pyramid map, and the face area of the...
Embodiment 2
[0072] Such as image 3 As shown, a non-contact heart rate measurement system based on face video images has the following modules:
[0073] Image acquisition module 1, used to collect video, and be divided into multi-frame RGB images;
[0074] The face feature extraction module 2 is used to extract image face feature points, determine the face area of interest, and perform spatial pixel averaging on the green channel to obtain an average value;
[0075] The background area extraction module 3 is used to extract the background area of interest in the image, and perform spatial pixel averaging on the green channel to obtain an average value;
[0076] The integration module 4 is used to integrate the pixel average value of each frame of RGB image to obtain an effective signal flow and a reference noise signal flow;
[0077] The signal flow processing module 5 is used to normalize the effective signal flow and the reference noise signal flow;
[0078] The denoising module ...
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