AP 186 Activity 10: Binary Operations

This is a culminating activity of all the methods we have learned so far. We are to get the area of normal cells and be able to discriminate cancer cells (which are really just abnormal cells) as very important application of image processing.

First, a little practice. We are given an image with punched circles. This is to measure the average size of a punched circle.The image is segmented and binarized for simplicity. However, there are still unwanted specks in the image. We use the morphological operations opening and closing to remove these unwanted attributes.

Fig 1. Counterclockwise from top left: original segment, black and white conversion, 

cleaning by morphological operators, cleaning using bwlabel.

To keep track of the blobs, we use bwlabel. It turns out that this function is very useful in not only identifying the number of blobs in the image but also in indexing these blobs. I used the sample code in the bwlabel Help article to get rid of other smaller (those left from opening and closing perhaps) and larger (stacks of cells) articles in the image.

Fig 2. The same segment as in Fig. 1 but here the blobs are filtered and labeled.

From the counted an indexed blobs, the cell areas were tallied. My computed average circle area is: 575.31 pixels. This is now used to isolate the 'cancer' cells in the given image Cells_with_cancer.jpeg.

Fig 3. Image of cells with cancer cells (left) and image of isolated cancer cells (right).

--
Thanks to BA and Che, my 'seatmates' in 186. :)
AP 186 Handout
Scilab Help
--
I give myself 10 in this activity because I did what has to be done and I enjoyed making this activity.