Efficiency issues with regards to image processing and character recognition

Question

0.00/5 (No votes)

See more:

binarization of an image is n^2.
blob detection is possibly n^2.
computation of image moments is also n^2.
feature extraction is also n^2.
clssification takes a long time given that our backpropagation
has 32-100-4 input, hidden and output units respectivelty.

is it even possible for us to solve a real-time character recognition
problem in less than 10 frames per second?

Posted 10-May-11 4:35am

Lady Malie

Add a Solution

1 solution

Add a Solution

Add your solution here

Treat my content as plain text, not as HTML

Preview 0

…

Existing Members

Sign in to your account

...or Join us

Download, Vote, Comment, Publish.

Your Email
Password
Forgot your password?

Your Email
This email is in use. Do you need your password?
Optional Password

I have read and agree to the Terms of Service and Privacy Policy
Please subscribe me to the CodeProject newsletters

When answering a question please:

Read the question carefully.
Understand that English isn't everyone's first language so be lenient of bad spelling and grammar.
If a question is poorly phrased then either ask for clarification, ignore it, or edit the question and fix the problem. Insults are not welcome.
Don't tell someone to read the manual. Chances are they have and don't get it. Provide an answer or move on to the next question.

Let's work to help developers, not make them feel stupid.

This content, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

Olivier Levrey · Answer 1 · 2011-05-10T04:53:00

You would be surprised to know what a (recent) computer can do in a little time.

If your images are not too big and all your algorithms "only" n^2, then go on.

In my job I personnaly handle 1000*750 images (16 bits per pixel) at a rate > 40 frames/second. I am doing a few processes for each frame, saving data on disk on the fly and so on...