TimK's profile - activity

@theodore That only works on pictures with a top down perspective. I've added a new photo (see edit), to illustrate what I mean and hopefully clear things up! Thanks for you comment.

I appreciate your answer. I might have not been clear enough, but I need it to work with any perspective. Please take a look at the last photo in my question (which I edited in).

@LBerger How would I do that?

I want to automate a process where text is recognized from a specific card type:

I will first explain what I dit so far. First I converted the image to a grayscale one:

Then I applied Canny:

By the result of this, it was easy to find the largest contour:

So far so good. The problem is: I have a shape here which fits in rectangle. However, the perspective is not top-down. Which implies that it is not possible to use boundingRect. Basically I'm in need of an algorithm to find the orientation of this contour.

I have no idea how to do this. Is there something I am missing? How would you do this?

Edit: Note that the above photo is not a good example, let me add another test case:

<uchar> is a template parameter for a template function. uchar means probably unsigned char as a typedef. Search for more info about c++ template functions.

I'm trying to automate a process where someone manually converts a code to a digital one.

Then I started reading about OCR. So I installed tesseract OCR and tried it on some images. It doesn't even detect something close to the code.

I figured after reading some questions on stackoverflow, that the images need some preprocessing like skewing the image to a horizontal one, which can been done by openCV for example.

Now my questions are:

• What kind of preprocessing or other methods should be used in a case like the above image?
• Secondly, can I rely on the output? Will it always work in cases like the above image?

I hope someone can help me!