Batch Processing of Multiple Input Folders

[degussa]

There ImageJ experts,
I am a beginners in writing macros, I want to perform the following process in ImageJ, but the present macro I have only process a single set of files from the folders and stops even though I have it set up in batch mode

1 Open three different folders with equal number of serialized images
2 Pick images with the same serial number eg, image C_001, B_001, C_001 from folders A, B, C
3 Stack of images picked with the same serial number above,
4           Find the standard deviation of the stack and save as a new image to another directory
5 Repeat steps 1 to 4 until all the images in the folders are processed


This is the Macro I presently wrote which does not run all the images

requires("1.33s");
dir1 = getDirectory("Choose the Directory for the reference images");
dir2 = getDirectory("Choose the directory for time series images=1");
dir3 = getDirectory("Choose the directory for time series images=2");
dir4 = getDirectory("Choose a directory for Difference images ");
  Dialog.create("SET UP INPUT PARAMETERS");
  Dialog.addMessage("PROVIDE A NAME FOR THE OUTPUT TEXT FILE");
  fname = "file name";
  Dialog.addString("File Name:", fname);
  Dialog.addMessage("DATASET IMAGE FILE EXTENSION");
  Dialog.addString("Reference Image File Extension:", ".tif");
  Dialog.addString("Time Series Image File Extension:", ".tif");
  Dialog.addString("Time Series Image File Extension:", ".tif");
  Dialog.show();
  fname = Dialog.getString();
  f = File.open(dir3+fname+".txt");
  exten1 = Dialog.getString();
  exten2 = Dialog.getString();
  exten3 = Dialog.getString();

  setBatchMode(true);  // prevents display of images

  list1 = getFileList(dir1);
  list2 = getFileList(dir2);
  list3 = getFileList(dir3);
  count = 0;
// Loop over the reference images

   for (i=0; i<list1.length; i++) {
                path1 = dir1+list1[i];
                open(path1); // Reference Dataset
            showProgress(count++, list1.length);
            t1 = getTitle();
                IDa = getImageID();

    run("Set Scale...", "distance=0 known=1 pixel=1 unit=inch");
//  Loop over the time-series images
        for (j=0; j<list2.length; j++) {
                  path2 = dir2+list2[j];
                open(path2); // Time-series Dataset
         IDb = getImageID();
           t2 = getTitle();
         run("Set Scale...", "distance=0 known=1 pixel=1 unit=inch");
//  Loop over the time-series images
        for (k=0; k<list3.length; k++) {
                  path3 = dir3+list3[k];
                open(path3); // Time-series Dataset
         IDc = getImageID();
           t3 = getTitle();
         run("Set Scale...", "distance=0 known=1 pixel=1 unit=inch");
                run("Images to Stack");
         IDd = getImageID();
         run("Z Project...", "start=1 stop=2 projection=[Standard Deviation]");
         selectImage(IDd);
         close();
         run("Specify...", "width=512 height=512 x=256 y=256 oval");
         run("Measure");
         meanstdDev = getResult("Mean", 0);
         stdDev =getResult("StdDev",0);
         print(t1+" ,"+t2+" , "+t3+", "+meanstdDev+", "+stdDev);    
         print(f,t1+" ,"+t2+" ,"+t3+", "+meanstdDev+", "+stdDev);
         run("Select None");
         run("Clear Results");  

 // The name is assigned to the output file
                outputname = "Stdev_"+t3;
                rename(outputname);
//                saveAs("Text Image", dir4+outputname+".txt");
                saveAs("Tiff", dir4+outputname+".tif");
                IDe = getImageID();
         selectImage(IDe);
         close();
                }  
        }
}
   File.close(f)
   print(count+" files processed");
   print("All done");