Programming

Finished reading the tutorial documentation for python. Finally found a 64bit version of JIL for python 2.6.

Ran through some of the documentation for that, and got a little ways.

It appears Python is very useful for images, quick short commands to change what you need. I don't know how well anything else will work in python when it comes to trying to measure the images' segmented objects; if it can even segment the objects.

Original Image

Image converted to grayscale, and then converted to binary with a threshold of 128.

im = Image.open("image.tif").convert("L").point(lambda i: i >= 128 and 255 or 0)

Another way of converting to binary/gray scale. Image didn't go all white and black.

im = Image.open("image.tif").convert("1").point(lambda i: i >= 128 and 255 or 0)

Image remained RGB, did the threshold of 128.

im = Image.open("image.tif").point(lambda i: i >= 128 and 255 or 0)

I tried working with JMF, and "Marvin's Framework"

http://marvinproject.sourceforge.net/en/index.html

There is a lot of documentation; it could be useful, will look at getting this set up to use and test.

Built a plugin usable for ImageJ; The plugin doesn't do much other than converting the image to grayscale, finding the edges, and converting that to binary with a threshold of 128.

Java built ImageJ Plugin function ran. See code.

Seems like it's an easy to use utility, documentation is well written for ImageJ.

        IJ ij = new IJ();
        Image i = ij.getImage().getImage();
       
        BufferedImage buffImage = new BufferedImage(i.getWidth(null),i.getHeight(null),BufferedImage.TYPE_BYTE_GRAY);
        Graphics g = buffImage.getGraphics();
        g.drawImage(i,0,0,null);
        g.dispose();
        Image im = buffImage;
        ij.getImage().setImage(im);
       
        ImageProcessor IP = ij.getImage().getProcessor();
        IP.findEdges();
        ByteProcessor BP = (ByteProcessor) IP.convertToByte(false);
        BP.threshold(128);
        ij.getImage().repaintWindow();