Wireless Communications and Mobile Computing

Research Article

Research on Carbon Foam Image Segmentation Based on Deep Learning

Algorithm 1

Convex hull construction and bidirectional selection rotation calipers algorithm-based carbon foam diameter calculation.
Input: points set of carbon foam: S1 = {P[n] = (P[n]. x, P[n]. y)}.
Output: the maximum diameter of each carbon foam.
Initialization: U and L as distance thresholds between two points; Cross as the cross product.
1:  Set the value of U and L;
2:  M_temp: =0; j: = n-i;
begin
 for i: =0 to n/2 do
 begin
  while Cross(P[i+1] - P[i], P [(k: =1) +1] – P[i]) > Cross(P[i+1] - P[i], P[k] – P[i]) do
  begin
   k = (k+1) % n;
   M = max (M_temp, max (the distance between P[i], P[k] and P[i+1], P[k+1]));
  end
  if L≤M≤U then
  begin
   delete P[k+1];
   M = M_temp;
  end
   M_temp = M;
 end
3:   Operation in the reverse direction;
   while Cross(P[j+1] - P[j], P [k+1] – P[j]) > Cross(P[j+1] - P[j], P[k] – P[j]) do
   begin
    k = (k+1) % n;
    M = max (M_temp, max (the distance between P[j], P[k] and P[j+1], P[k+1]));
end
   if L≤M≤U then
   begin
    delete P[k+1];
    M = M_temp;
   end
   M_temp = M;
 end
4:   Get the Convex Hull (CH).
5:   Get points set of Convex Hull: S2 = {P[n]/Q[n] = (P[n]/Q[n]. x, P[n]/Q [n]. y)};
6:   Find the convex hull's two extreme points: P1[n] and Q1[n], Construct two horizontal lines of support through P1[n] and Q1[n];
7:   Compute the distance between P1[n] and Q1[n], and mark it as Distance;
8:   Rotate the lines until one is flush with an edge of CH, and obtain an anti-podal pair;
9:   compute the distance, and mark it as Distance_temp;
 begin
  while anti-podal pair! = P1[n] and Q1[n] do
   if Distance_temp > Distance then
    Distance: = Distance_temp
 end
10:   Determining the maximum as the diameter pair(s).