Patent ID: 11967123
Assignee: XIDIAN UNIVERSITY
Field: Audio-visual technology (Electrical engineering)
Classification: CPC G  H  Y | IPC G  H

Claim 0:
1. A binarization method for computed tomography (CT) sectional image of fiber package containing artifacts, comprising:
step 1, inputting a source image I of a CT sectional image of fiber package containing artifacts, converting the source image I into a hue-saturation-value (HSV) image model, and performing brightness adjustment on the source image I obtained after converting of the HSV image model to thereby obtain a first intermediate image I1;
wherein the step 1 specifically comprises:
step 1.1, defining a brightness value of each pixel of the source image I as V, and V∈ [0, 255];
step 1.2, drawing a brightness distribution histogram of the source image I to thereby obtain a range [a, b] of a brightness value Vgx of a fiber region of the fiber package, a maximum value M of the brightness value Vgx, and a range [a′, b′] of a brightness value V range of a region of the fiber region most affected by the artifacts; and
step 1.3, performing, based on a composite tangent function and according to a formula 1.1, nonlinear brightness adjustment on each pixel of the source image I obtained after converting of the HSV image model, to thereby obtain the first intermediate image I1:

V′=V−A tan(BV+φ)  (formula 1.1),

where V′ represents a lightness value after nonlinear brightness adjustment, V represents the brightness value before nonlinear brightness adjustment, A represents a range control coefficient, B represents an adjustment coefficient of lightness control range, and φ represents an origin-point control coefficient;

wherein in the step 1.3,
the composite tangent function is a part of a tangent function in a range of [−3 T/8, 3 T/8], T represents a period of the tangent function;
the range control coefficient A satisfies a formula 1.2:, A
      <
      
       
        
         2
         ⁢
         5
         ⁢
         5
        
        -
        M
       
       
        tan
        ⁡
        (
        
         
          3
          ⁢
          T
         
         8
        
        )
       
      
     
     ;
    
   
   
    
     (
     
      formula
         
      1.2
     
     )
    
   
  
 

the adjustment coefficient of lightness control range B satisfies a formula 1.3:, 3
        ⁢
        T
       
       
        4
        ⁢
        
         (
         
          
           2
           ⁢
           
            a
            ′
           
          
          -
          a
          -
          b
         
         )
        
       
      
      <
      B
      <
      
       
        3
        ⁢
        T
       
       
        1
        ⁢
        0
        ⁢
        2
        ⁢
        0
       
      
     
     ;
     and
    
   
   
    
     (
     
      formula
        
      1.3
     
     )
    
   
  
 

the origin-point control coefficient co satisfies a formula 1.4:, φ
      =
      
       
        -
        B
       
       ⁢
       
        
         a
         +
         b
        
        2
       
      
     
     ;
    
   
   
    
     (
     
      formula
         
      1.4
     
     )
    
   
  
 

step 2, creating a planar morphological structural element SE having a morphology similar to that of a target object, and deleting a subject not containing the planar morphological structural element SE in the first intermediate image I1 to thereby obtain a background image Ib without the target object;
step 3, replacing a background of the first intermediate image I1 with a black background by performing a subtraction operation on pixels of the first intermediate image I1 and pixels of the background image Ib, to thereby obtain a second intermediate image I2, wherein the second intermediate image I2 is obtained by a formula 3.1 expressed as follows:

I2=I1−Ib  (formula 3.1);

step 4, expanding a gray value change interval of a main region of the second intermediate image I2 to improve an image contrast of the second intermediate image I2 and thereby obtain a third intermediate image I3;
step 5, binarizing the third intermediate image I3 by using a local adaptive threshold binarization algorithm, to thereby obtain a binarized image I4;
wherein the step 5 specifically comprises:
step 5.1, when different neighborhood radii are selected, calculating a relative difference Δ between a connected domain number nr and an actual section number N of an optical fiber core in a same region according to a formula 5.1, and adaptively obtaining an optimal neighborhood radius r required by the local adaptive threshold binarization algorithm for achieving an optimal binarization effect:, △
      =
      
       |
       
        
         
          n
          r
         
         -
         N
        
        N
       
       |
      
     
     ;
    
   
   
    
     (
     
      formula
         
      5.1
     
     )
    
   
  
 

step 5.2, calculating a gray mean m(x, y) and a standard variance s(x, y) in a neighborhood of r×r of each pixel of the third intermediate image I3 according to a formula 5.2 and a formula 5.3, respectively:, m
       ⁡
       (
       
        x
        ,
        y
       
       )
      
      =
      
       
        1
        
         r
         2
        
       
       ⁢
       
        
         ∑
         
          i
          =
          
           x
           -
           
            r
            2
           
          
         
         
          x
          +
          
           r
           2
          
         
        
         
        
         
          ∑
          
           j
           =
           
            y
            -
            
             r
             2
            
           
          
          
           y
           +
           
            r
            2
           
          
         
         
          g
          ⁡
          (
          
           i
           ,
           j
          
          )
         
        
       
      
     
     ;
    
   
   
    
     (
     
      formula
         
      5.2
     
     ), s
       ⁡
       (
       
        x
        ,
        y
       
       )
      
      =
      
       
        
         1
         
          r
          2
         
        
        ⁢
        
         
          ∑
          
           i
           =
           
            x
            -
            
             r
             2
            
           
          
          
           x
           +
           
            r
            2
           
          
         
         
          
           ∑
           
            j
            =
            
             y
             -
             
              r
              2
             
            
           
           
            y
            +
            r
           
          
          
           
            (
            
             
              g
              ⁡
              (
              
               i
               ,
               j
              
              )
             
             -
             
              m
              ⁡
              (
              
               x
               ,
               y
              
              )
             
            
            )
           
           2
          
         
        
       
      
     
     ;
    
   
   
    
     (
     
      formula
         
      5.3
     
     )
    
   
  
 

where g(i, j) represents a gray value of each pixel in the neighborhood of r×r; and
step 5.3, calculating a binarization threshold T(x, y) of each pixel in the neighborhood of r×r according to a formula 5.4, and obtaining a binarized image I4:

T(x,y)=m(x,y)+z·s(x,y)  (formula 5.4),

where z represents a denoising coefficient, which is preset by experience; and

step 6, removing a background noise of the binarized image I4 to thereby obtain a final binarized image I5.