diff --git a/script/LedDetectionFilter.py b/script/LedDetectionFilter.py
index 81dcbd7..719551d 100644
--- a/script/LedDetectionFilter.py
+++ b/script/LedDetectionFilter.py
@@ -1,4 +1,100 @@
-run ("LedDetection")
+################################################################################################### 
+# Example of using ImageJ functionalities through ijutils.
+################################################################################################### 
+
+import datetime
+from ijutils import *
+import java.awt.Color as Color
+
+import ch.psi.pshell.imaging.Filter as Filter
+from ch.psi.pshell.imaging.Overlays import *
+import ch.psi.pshell.imaging.Pen as Pen
+
+
+roi_center = (800, 600)
+roi_radius = 600
+integration_count = 10
+integration_continuous = False
+integration_partial = False
+frames = []            
+
+roi = (roi_center[0] - roi_radius, roi_center[1] - roi_radius, 2* roi_radius, 2*roi_radius)
+
+
+color_roi = Color(0, 128, 0)
+
+renderer = show_panel(img)
+renderer.clearOverlays()
+ov_roi_shape = Ellipse(Pen(color_roi, 0,), java.awt.Point(roi[0], roi[1]), java.awt.Dimension(roi[2], roi[3]))       
+ov_roi_bound = Rect(Pen(color_roi, 0, Pen.LineStyle.dotted), java.awt.Point(roi[0], roi[1]), java.awt.Dimension(roi[2], roi[3]))       
+ov_roi_center = Crosshairs(Pen(color_roi, 0),  java.awt.Point(roi_center[0],roi_center[1]), java.awt.Dimension(15,15))
+
+renderer.addOverlays([ov_roi_shape, ov_roi_bound,ov_roi_center])
+
+
+def in_roi(x,y):
+    return math.hypot(x-roi_radius, y-roi_radius) < roi_radius
+
+
+def integrate (ips):    
+    for i in range(len(ips)):
+        if i==0:
+            aux = new_image(roi[2], roi[3], image_type="float", title = "sum", fill_color = None)
+        op_image(aux, ips[i], "add", float_result=True, in_place=True)
+    op_const(aux, "divide", len(ips), in_place=True)
+    return aux
+
+
+last_ret = (None, None)
+def detect_led(ip):
+    global roi_center, roi_radius, integration_count, integration_continuous, integration_partial, frames
+    global count , last_ret 
+    aux = sub_image(ip, roi[0], roi[1], roi[2], roi[3])
+    grayscale(aux)
+    #gaussian_blur(aux)
+    if (integration_count>1):             
+        frames.append(aux)        
+        if len(frames) >integration_count:
+            del frames[0]        
+        if not integration_continuous:            
+            if (len(frames)< integration_count):                
+                if last_ret[1] is not None: invert(last_ret[1])                
+                return last_ret                   
+        if (not integration_partial) and len(frames) <integration_count:            
+            return last_ret
+        aux = integrate(frames)
+    
+    #aux = get_channel(aux, "blue")
+    invert(aux)
+    #subtract_background(aux) 
+    #Tested ok: Huang, Mean, MaxEntropy, Percentile, Triangle, Yen
+    auto_threshold(aux, method = "Percentile")
+    #binary_open(aux)
+    (results,output) =  analyse_particles(aux, 250,1000, 
+            fill_holes = True, exclude_edges = False, print_table=False,
+            output_image = "outlines", minCirc = 0.3
+            , maxCirc = 1.0)
+    r=results
+
+
+    points = ""
+    npoints = 0
+    for row in range (r.counter):
+        if in_roi(r.getValue("XM",row), r.getValue("YM",row)):
+            points = points + " (" + str(int(r.getValue("XM", row))+roi[0]) + ", "  + str(int(r.getValue("YM", row))+roi[1]) + ")"
+            npoints = npoints + 1
+    print str(npoints) + " - " + points
+        
+    last_ret = (results,output)
+    if not integration_continuous:
+        frames = []  
+
+    #if npoints!=12:        
+    #    save_image(op_image(aux, output,"xor", in_place=False),  "{images}/" + str(datetime.datetime.now().strftime("%Y%m%d_%H%M%S"))+".png", "png")        
+    #return (results,aux)    
+    return (results,output)
+
+
 
 
 ip = None
@@ -15,4 +111,5 @@ class MyFilter(Filter):
         return ip.getBufferedImage()
 
 #Setting the filter to a source
-img.setFilter(MyFilter())
\ No newline at end of file
+img.setFilter(MyFilter())
+