diff --git a/worker.py b/worker.py
old mode 100644
new mode 100755
index c59c7b8..db8bf53
--- a/worker.py
+++ b/worker.py
@@ -1,4 +1,4 @@
-#! /usr/bin/python3
+#! /usr/local/bin/python3
 from io import BytesIO
 from numpy import asarray
 from PIL import Image
@@ -39,26 +39,97 @@ while data :
 
     # Trace the bitmap to a path
     path          = bmp.trace(turdsize=16,alphamax=0.0, opticurve=0, opttolerance=1.0)
+
+
+    # Record the min/max coordinates and a list of points 
+    min_x         = 0
+    min_y         = 0
+    max_x         = -9999
+    max_y         = -9999
+
     pl            = []
+    pl_index      = 0
+    odd_indices   = []
+    def plappend( point ):
+      global pl, pl_index, odd_indices, min_x, min_y, max_x, max_y
+      pl.append(point)
+      pl_index    += 1
+      suspect     = False
+      
+      if point[0] <= min_x : 
+        min_x     = point[0]
+        suspect   = True 
+      if point[0] >= max_x : 
+        max_x     = point[0]
+        suspect   = True 
+      if point[1] <= min_y : 
+        min_y     = point[1]
+        suspect   = True 
+      if point[1] >= max_y : 
+        max_y     = point[1]
+        suspect   = True 
+      if suspect == True:   
+        odd_indices.append(pl_index)
+        return True
+      return False
+
 
     for curve in path:
       start     = curve.start_point
-      pl.append([int(start[0]),int(start[1]),0])
-      pl.append([int(start[0]),int(start[1]),color])
+      plappend([int(start[0]),int(start[1]),0])
+      plappend([int(start[0]),int(start[1]),color])
       for segment in curve:
         end_point_x, end_point_y = segment.end_point
         if segment.is_corner:
           c_x, c_y = segment.c
-          pl.append([int(c_x),int(c_y),color])
+          plappend([int(c_x),int(c_y),color])
           pass
         #
         else:
           c1_x, c1_y = segment.c1
           x, y = segment.c2
-          pl.append([int(x),int(y),color])
-          pl.append([int(c1_x),int(c1_y),color])
+          plappend([int(x),int(y),color])
+          plappend([int(c1_x),int(c1_y),color])
       #
-      pl.append([start[0],start[1],0])
+      plappend([int(start[0]),int(start[1]),0])
+
+    # Run the border detection
+    def isBorder( pt ):
+      result = []
+      # calculate the distance to min/max
+      min_x_dst = abs(min_x - pt[0])
+      max_x_dst = abs(max_x - pt[0])
+      min_y_dst = abs(min_y - pt[1])
+      max_y_dst = abs(max_y - pt[1])
+      if min_x_dst <= 1 :
+        result.append("min_x")
+      if max_x_dst <= 1 :
+        result.append("max_x")
+      if min_y_dst <= 1 :
+        result.append("min_y")
+      if max_y_dst <= 1 :
+        result.append("max_y")
+      return result
+
+    deleteList = []
+    for i in range(len(odd_indices) - 1) :
+        ind             = odd_indices[i]
+        pt              = pl[ind]
+        nextpt          = pl[ind+1]
+        # Early skip black points
+        if 0 == pt[2] or 0 == nextpt[2]:
+            continue
+        pt_is_bord      = isBorder(pt)
+        nextpt_is_bord  = isBorder(nextpt)
+        if 0 == len(pt_is_bord) or 0 == len(nextpt_is_bord):
+            continue
+        #print( "{} and {} are border.".format(pt,nextpt))
+        deleteList.append(ind)
+        deleteList.append(ind+1)
+
+    deleteList = sorted(set(deleteList), reverse=True)
+    for i in deleteList:
+        pl[i] = [pl[i][0],pl[i][1],0]
     item["points_list"] = pl
     item["created_at"]  = time.time()
     r.hset("images",hash_name, json.dumps(item))