CODEWITHSUNDEEP
image-processingopencvcomputer-vision
user189320
user189320

Reputation:

How to detect exact, predefined shapes with hough transform, like a "W"?

Let's say I have some system that scans documents, where all documents use the same font and font size.

In these documents, there will always be the same looking letter "W". Let's say it is always 20 px large. How can I set up the hough transform to recognize this letter "W" at 20 px large in my documents?

Upvotes: 6

Views: 632

Answers (2)

Rethunk
Rethunk

Reputation: 4113

The Hough transform for lines finds best fit line equations. You would need to do additional processing to find just the line segments. If the character thickness is several pixels, then to effectively find lines you might want to reduce the thickness to one pixel. There are techniques to do that, but also various algorithmic traps.

Once you have your line segments, you would still have to write an algorithm to identify characters based on the relative position and angle of the line segments. It's harder than it first appears.

A normalized cross-correlation (template matching) could work if you're certain that the image will always be in a certain rotation, the characters will always be the same size, etc. But even for scans you'll see some rotation and some variation in contrast.

All that aside, it's likely cheaper in the long run to use a commercial OCR package or reasonably good open source project. OCR is hard to implement if you're not already familiar with image processing.

Upvotes: 1

mevatron
mevatron

Reputation: 14021

A quick Google search yields the following information of interest:

Generalizing the Hough Transform to Detect Arbitrary Shapes

and it looks like a lecture using the above paper as its source.

Also, if it's an actual "W", would an OCR engine like Tesseract be better suited to your needs?

Upvotes: 3

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