A method, device, and computer-readable storage medium for sclera recognition
An identification method and sclera technology, applied in computer parts, computing, acquisition/recognition of eyes, etc., can solve problems such as poor user experience, difficult software and hardware development, and narrow application range of biometric technology, and achieve wide application conditions, Low development difficulty and good user experience
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Embodiment 1
[0101] A method for identifying sclera, the method comprising:
[0102] S1. Obtain and process the eye image to obtain a grayscale image of the sclera;
[0103] S2. Determine the feature points in the grayscale image of the sclera;
[0104] S3. Determine the system feedback value according to the feature points;
[0105] S4. Matching the system feedback value and the preset comparison value, and feeding back the sclera recognition result.
[0106] In this embodiment, first, the eye image is acquired and processed to obtain a grayscale image of the sclera. Among them, the sclera is the outermost layer of the eyeball wall, which is composed of dense collagen and elastic fibers. Its structure is tough, opaque, hard and magnetically white. The sclera is also the object of analysis and processing in this program.
[0107] Then, process the eye image to obtain a grayscale image of the sclera, wherein the grayscale of the image can be in the RGB model, if R=G=B, then the color re...
Embodiment 2
[0116] Based on the above-mentioned embodiments, the acquisition and processing of the eye image to obtain the grayscale image of the sclera includes:
[0117] S11. Obtain an image to be identified;
[0118] S12. Determine the eye image in the image to be recognized according to the eye features;
[0119] S13. Extract the eye image, and process the eye image according to preset grayscale features;
[0120] S14. Extract the color information of the eye image to obtain the grayscale image of the sclera.
[0121] In this embodiment, first, acquire the image to be recognized, for example, Figure 4 The grayscale image of the sclera shown, the grayscale image of the sclera includes the orbital area, the eyeball area, the left block area and the right block area; then, according to the eye features, determine the eye image in the image to be recognized ,E.g, Figure 4 The above is the eye area, wherein the eye area is composed of the orbital area, the eyeball area, the left bloc...
Embodiment 3
[0124] Based on the above-mentioned embodiments, the determination of the feature points in the grayscale image of the sclera includes:
[0125] S21. Determine a preset binarization algorithm;
[0126] S22. Determine the feature points in the grayscale image of the sclera according to the binarization algorithm.
[0127] In this embodiment, firstly, the preset binarization algorithm is determined, wherein, the binarization of the image is to set the grayscale value of the pixel on the image to 0 or 255, that is, to present the whole image with a distinct Only black and white visual effects. An image includes the target object, background and noise. To directly extract the target object from a multi-valued digital image, the most common method is to set a global threshold T, and use T to divide the image data into two parts: A pixel group larger than T and a pixel group smaller than T. The pixel value of the pixel group larger than T is set to white (or black), and the pixel...
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