Ring-shaped object counting method based on image processing
A ring-shaped object and image processing technology, applied in the field of image processing, can solve problems such as difficulties, achieve the effects of light weight, overcome setting difficulties, missed detection, and avoid accumulated errors
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[0038] Step 1. Image preprocessing
[0039]1-1 Grayscale: The RGB three components of the color image are weighted and averaged with different weights. A weighted average of the RGB three components can be obtained by the following formula to obtain a more reasonable grayscale image f(i, j) = 0.30R(i, j) + 0.59G(i, j) + 0.11B(i, j);
[0040] 1-2 Binarization: The OTSU algorithm is used, that is, the gray value with the largest variance between classes is selected as the optimal segmentation threshold, and the image is binarized to obtain the image src_th (the ring part is 1 (white) and the rest is 0 (black)).
[0041] 1-3 distance transformation: perform distance transformation on the image src_th.
[0042] 1-4 Watershed algorithm: Use the watershed algorithm to segment the image after distance transformation to obtain the image src_line with the dividing line, and find the outer contour contours of the image src_line, and the number of contours is n.
[0043] Step 2, extra...
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