Hericium erinaceus nondestructive test grading method based on machine vision
A computer vision and non-destructive testing technology, applied in computer parts, computing, image analysis, etc., can solve the problems of scattered, little research, and no Hericium erinaceus detection method, and achieve the effect of accurate detection and avoidance of damage
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[0018] The specific steps of the computer vision-based non-destructive testing and grading method for Hericium erinaceus in this embodiment are as follows:
[0019] The first step, feature parameter extraction - select a group of Hericium erinaceus with no spots, no disease, and no damage, clean up the dirt on its surface as a training sample, and use a SLR camera to take a true-color image of Hericium erinaceus cap overlooking (that is, 24-bit RGB color image), each pixel value of the image is divided into three primary color components of R, G, and B, and each component has 256 gray values.
[0020] after
[0021] 1. Extract feature factor preprocessing (see figure 1 — Figure 4 )
[0022] Grayscale - convert the ingested true-color image to a grayscale image;
[0023] Noise reduction - mean filtering or median filtering removes noise in the image, making it a smooth image;
[0024] Binarization - set the gray value of the pixel on the smooth image to 0, 255, making it ...
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