CODEWITHSUNDEEP
c#.netalgorithmmathimage-processing
Mac Sigler
Mac Sigler

Reputation: 189

How to find rotation angle of image?

I'm feeding in a Bitmap image to my C# program to be able to perform OCR to identify the characters in the image. I can do this fairly well if the image is not rotated. One of the program requirements, however, is that the program automatically determines if the image has been rotated, and that it automatically corrects these rotations.

I've tried implementing a simple method where lines are traced across the image and points which contact a character are recorded, and then performing a simple linear regression on the line points. This works to an extent, although it has not proven very accurate due to curvature of characters, etc.

I was wondering if there was a better method to solve this problem? Many thanks in advance! :)

Upvotes: 9

Views: 5968

Answers (6)

Shadi_Naser
Shadi_Naser

Reputation: 1

We faced a similar problem before, and we searched for an easy and quick solution, and we ended up using a commercial toolkit (leadtools). You can use it to do auto processing to the image before OCR it. You can check this help topic to know how to use this toolkit to process and scan images.

Upvotes: 0

nguyenq
nguyenq

Reputation: 8345

I use gmseDeskew algorithm to deskew an image in my program. It works very well.

Upvotes: 2

Noremac
Noremac

Reputation: 3547

If the text is formatted like a printed document (column(s) and lines of text) then you can take advantage of this.

An approach that I've often seen used for document text is to do projection profiles:

  1. Scan a document at a specific orientation and sum up the number of "black" pixels on each scan line (creating a 1D array of counts, each index representing a Y coordinate, the profile).
  2. Calculate the variance of the counts (profile).
  3. Repeat for multiple angles, (can be done in a binary search fashion to reduce processing)
  4. The angle that results in the greatest variance is the correct angle (due to the text lines creating large peaks from the printed text, and low valleys due to the absence of text between the lines)

Then after finding this angle you can adjust your image accordingly and do your awesome OCR.

Upvotes: 1

maxim1000
maxim1000

Reputation: 6365

If it recognizes lines of text, then try to blur the image so that lines are mostly solid and find direction of the lines (either with analysis of Fourier transform or by ridge detection).

Upvotes: 2

Adrian McCarthy
Adrian McCarthy

Reputation: 47954

It might be easier to find the vertical-ish lines that are adjacent to the text (i.e., the left margin). For each scanline, record the first black pixel. Put all of those in a linear regression, and you should get a near vertical line. Measure its angle from true vertical and you should be able to unrotate the text. You could imagine doing the same thing for the top, bottom, and right sides, too, and taking an average.

Upvotes: 0

Heather
Heather

Reputation: 2652

It's an interesting problem to be sure. I'd look for certain letters that are easier to tell rotation for. For example, a capital A or R or K should have both of the lower parts are roughly the same horizontal plane. Another option is to take letters that cannot be identified and rotate them in various ways and re-attempt to identify them. If a letter than could not be identified in the raw scan CAN be identified when you rotate it, that's a pretty big clue. Once you have identified the "correction" rotation that makes a non-recognizable character into a recognizable one, apply the same rotation value to the others.

Upvotes: 2

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