Description
Introduction
In this assignment we will investigate an image processing application.
Analyzing blood smear images, and extracting features of the cells is an important application in the field
of medicine to help detect and monitor various types of diseases. In this assignment, you will implement
a simple form of red blood cell counting. This assignment was inspired by an article
(https://www.sciencedirect.com/science/article/pii/S2352340915001626?via%3Dihub#bib1) about a data set
and algorithm for counting red blood corpuscles.
The images we originally started with were stored in BMP format.
We have already taken care of the first steps, so you will be working with a text file that has already been
segmented. We have taken the above image, and produced black and white images where all pixels
have the values of 0 (black) or 255 (white).
We then converted the file to ASCII (plain text) format so that you can read it using fscanf(). Read the
man page for fscanf() by typing man fscanf at the command line.
The file contains only integers separated by a space, and you can assume that the file format is correct
when writing your code. The first two integers (first line) are the number of rows and columns of the
image in pixels. There is a newline character after each row of pixels to make it slightly easier to visually
inspect the file.
Step 0: Set up
Your program will consist of two files: count_cells.c and image.c
These files have already been added to you repo. You should be able to compile your program using the
following gcc line:
gcc -Wall -g -std=gnu99 -o count_cells count_cells.c image.c
Step 1: Reading and writing an image file
The main function in count_cells.c takes one or two command-line arguments:
The first argument the name of blood cell image in the text file format described above.
The second argument, ” -p ” is optional. If present, this argument indicates that the pixel matrix
should be printed before other program output. In image.c you will implement two functions. Their
function prototypes are given below:
/* Reads the image from the open file fp into the two-dimensional array arr
* num_rows and num_cols specify the dimensions of arr
*/
void read_image(int num_rows, int num_cols,
int arr[num_rows][num_cols], FILE *fp);
void print_image(int num_rows, int num_cols, int arr[num_rows][num_cols]);
Because we are passing in a variable-length, multi-dimensional array as an argument to a function, the
first two arguments must be the dimensions of the array, and the third the array itself. (See King pages
197-199) We could call read_image as
int p, q; // assume p and q have valid values
int a[p][q];
FILE *fp; // assume fp holds a valid open file pointer
read_image(p, q, a, fp);
This means that we need to read the dimensions of the array before calling read image. Write these two
functions and call them from the main function in count_cells.c code and test it before moving on.
Remember to add the prototypes to count_cells.c . This might also be a good time to learn the basics
of gdb.
It would also be a great idea to make sure to commit and push your work at this point.
Step 2: Count cells
Write a function count_cells to count the number of blood cells in the image. One cell is a region of
adjacent white pixels. The function will be implemented in image.c
A pixel is adjacent to another pixel if there is a pixel of the same colour above, below, left or right of the
pixel. In the example image below there are 6 cells. The “blue cell” is composed of 5 pixels, the red cell
is composed of 6 pixels, the green cell is composed of 3 pixels (and has no pixels adjacent to the red
cell), and there are three pink cells of one pixel each.
The main function will call count_cells and will print a message to stdout using the following format
string:
“Number of Cells is %d\n”
You must include a statement using this exact format string to receive credit for your cell count. Be sure
to print this only once.
Exactly how you count these cells is up to you, but I’d like to direct your attention to the flood fill
algorithm, which is a recursive algorithm that recursively visits and somehow marks all adjacent pixels
starting at some seed pixel within (in our case) a cell. Recursion terminates whenever a pixel visited
does not have the same value as the seed pixel. This is how the paint-bucket works in any basic image
creation software.
If you use any other algorithm (e.g. authored and developed yourself) be sure to add comments. If you
decide to use some other algorithm described by someone else (note, you cannot copy any code in
any of these cases, but you can look up algorithms) be sure to include a clear citation in your code with
the author(s) names and how you accessed it.
Input
You probably want to create a few smaller image files so that you can verify that your algorithms are
working correctly, and so that you can test some edge cases. For example, here is one that I wrote: (I
will leave it to you to figure out how many cells are in this image).
4 7
0 0 255 255 0 0 0
0 255 0 0 255 255 0
0 255 0 0 0 0 0
255 255 0 0 0 0 0
There are a number of .bmp files and the resulting .txt files in /u/csc209h/fall/pub/a1 on teach.cs that
you can also use as input. Note that these aren’t that useful for testing, unless you want to count by hand
the number of cells in them.
What to submit
Add, commit, and push your image.c and count_cells.c files to the a1 directory in your repository.
Please refer to the Syllabus (https://q.utoronto.ca/courses/309775/pages/syllabus?wrap=1) to make sure
you are following the expectations for assignment submissions, mainly, never pushing your program’s
binaries to the repo and ensuring that it compiles.