Patent ID: 11887287
Assignee: PENGCHEN NEW MATERIAL TECHNOLOGY CO., LTD.
Field: Computer technology (Electrical engineering)
Classification: CPC G  Y | IPC G

Claim 0:
1. A production monitoring and analysis method based on an image data algorithm, comprising:
obtaining a gray image of an image where a product identification code is located, obtaining a reconstructed gray level of each pixel in a gray histogram according to a mean value of the gray level, a maximum gray level, a minimum gray level, and a gradient of each pixel in the gray image, and obtaining a reconstructed gray histogram according to the reconstructed gray level of each pixel in the gray histogram;
a specific expression of the reconstructed gray level of each pixel is as follows:, H
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    i
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  =
  
   
    
     
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      max
     
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      x
      min
     
    
    255
   
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wherein H(i,j) represents a reconstructed gray level of a pixel (i,j), xmax represents the maximum gray level, xmin, represents the minimum gray level, xij represents a gray level of a pixel (i, j), x represents the mean value of the gray level, and G(i,j) represents a gradient of the pixel (i,j) in the gray image;
obtaining a segmentation threshold of an Otsu algorithm for segmenting the reconstructed gray histogram, correcting the segmentation threshold to obtain a new segmentation threshold according to several pixels corresponding to each gray level in the reconstructed gray histogram, and segmenting the reconstructed gray histogram to obtain a sub-gray histogram according to the new segmentation threshold;
a specific expression of the new segmentation threshold is as follows:, Sp
  =
  
   
    x
    T
   
   +
   
    
     ∑
      
     
      
       n
       q
      
      ⁢
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wherein Sp represents the new segmentation threshold, nq represents a number of gray levels corresponding to a pixel q in the reconstructed gray histogram, Σnqq represents an area corresponding to the gray level in the reconstructed gray histogram, and xT represents the segmentation threshold;
obtaining a lateral segmentation threshold of the sub-gray histogram according to a total number of pixels in each sub-gray histogram and a length of a gray level interval of the sub-gray histogram, and obtaining an adjustment of the gray level in the sub-gray histogram according to the lateral segmentation threshold of the sub-gray histogram and all the gray levels greater than the lateral segmentation threshold; and
correcting the sub-gray histogram to obtain a corrected sub-gray histogram according to the adjustment of the gray level in the sub-gray histogram, the lateral segmentation threshold of the sub-gray histogram, and all the gray levels greater than the lateral segmentation threshold, obtaining an enhanced gray image according to the corrected sub-gray histogram, and identifying a recognition code in the enhanced gray image and completing a product classification.