Hi Steven,
When you mentioned that you looked into OCR, I assume you meant the "ocr" function in MATLAB, but if you haven't seen this doc page, thought it would be helpful to you:
However, I've done something similar without using the computer vision toolbox at all- if you know what the numbers will look like (for example, you take a screenshot of each of the numbers separately), you can essentially adapt what this person was doing for integer recognition:
This essentially entails creating a "test" image for each number as a training set, expanding that image and subtracting the original image so that it can test if the numbers are equivalent. This code in particular uses the binary hit-or-miss algorithm found here to identify the number. It recognizes the "left" or "right" of two digit numbers by just identifying which side of the image there is a match.
Attached is my adapted version of the File Exchange code with my own additions to it from when I used it for my project. I called that function within another function I named "process", which includes the following lines of code:
X= imread(File); %Read screenshot you want
im_gray = rgb2gray(X); %Convert to grayscale/1-channel image
im_bw = im2bw(im_gray,0.5); %Convert to black and white with threshold of 1/2
im_sub = im_bw(210:270,1636:1714); %Select region of interest for numbers
[Number]= intrec(im_sub); %Pattern recognition on the numbers (Integer recognition)
Output= Number; %Output the number
Hope this helps! It definitely makes it much easier that you know what the numbers should look like and where they would be.
