Optical character recognition program for photographs

5
votes

I need to develop an optical character recognition program in Matlab (or any other language that can do this) to be able to extract the reading on this photograph.

The program must be able to upload as many picture files as possible since I have around 40000 pictures that I need to work through.

The general aim of this task is to record intraday gas readings from the specific gas meter shown in the photograph. The is a webcam currently setup that is programmed to photgraph the readings every minute and so the OCR program would help in then having historic intraday gas reading data.

Which is the best software to do this in and are there any online sources that are available for this??

2
matlabocr
@Yochai Timmer The last line:P thank you about that.. - Apollon1954
What do you have under your control? i.e can you position the webcam as you see fit, can you extra lighting? - Ashish Uthama
@hash blue Yes, i have full control of the webcam and the lighting in the room - Apollon1954
If you're measuring every minute, you have a lot of extra information to use. If a character didn't change in the last N pictures but changed in this one, you can (probably) safely assume it went up by 1. Similarly, if you read the meter successfully at t1 and t3, but not t2, just take the average at times t1 and t3 and you're fine. - Dave

2 Answers

4
votes

I'd break down the basic recognition steps as follows:

  1. Locate meter display within the image
  2. Isolate and clean up the digits
  3. Calculate features
  4. Classify each digit using a model you've trained using historic examples

Assuming that the camera for a particular location does not move, step 1 will only need to be performed once. Step 2 will include things like enhancing contrast and filtering noise. Step 3 can include any useful calculations you can think of, such as mean and skew of "ink" (white) pixels. Step 4 would utilize a model you build to classify a single digit as '0', '1', ... '9', and could be accomplished using k-nearest neighbors, logistic regression, SVM, neural network, etc.

2
votes

A couple of things would make 1 in Predictor's answere easy: Placing the cam directly above the meter, adding sufficient light, maybe placing bright pink strips around the meter to help segment out the display :).

Once you do this, and the cam remains fixed, you can use a manual process once and then have it applied to all subsequent images to segment out the digits. If the lighting is good and consistent, you might just be able to use simple template matching to identify each of the segmented digits.

Actually, once you get a sample of all the digits, you might even be able to classify them on something simpler (like sum of thresholded pictures).