Coal dust image identification method
A technology of image recognition and dust, applied in character and pattern recognition, instruments, computer parts, etc., can solve the problems of low accuracy of segmentation algorithm and difficulty in fitting particles with more than 3 overlaps by clustering algorithm
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[0101] Such as figure 1 As shown, the coal dust image recognition method of the present invention includes the following steps:
[0102] Step 1: Use fuzzy rough set based on multi-attribute reduction to segment the coal dust image. The specific process is:
[0103] Step 101: Determine the membership degree of the fuzzy category: the image processor uses the acquired coal dust image as a fuzzy rough set Y={y 1 ,y 2 ,...,Y n′ } To deal with, in the fuzzy rough set Y = {y 1 ,y 2 ,...,Y n′ } Construct k′ clusters m 1 ,m 2 ,...,M k′ , And determine y i′ Corresponds to w i′ Fuzzy category membership
[0104] Where y i′ Is the gray value of the i′th pixel in the coal dust image, i′=1, 2,...,n′, n′ is the number of pixels, k′ is a non-zero natural number, w i′ Is the pixel in the universe U of the fuzzy rough set;
[0105] In specific implementation, the coal dust image processed by the image processor is obtained by using a microscope magnifier.
[0106] In this embodiment, the image pr...
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