CODEWITHSUNDEEP
c#image-processingaforge
Eddie
Eddie

Reputation: 78

Thick circle detection

I have an RGB image.Suppose say I have two circles in it.I want to know which one is filled and which one is not.I followed the following steps: -imported the image as Bitmap

rgbimage

-converted into grayscale and used CannyEdgeDetector filter to find the edges. I get the following image

edge

circle containing the letter "D" gives two edges, where as I need only one circle edge. Secondly, how do I find out which circle is filled and which one is not.

Upvotes: 2

Views: 1073

Answers (3)

Peter
Peter

Reputation: 2260

Perform blob detection, with a pixel count

or even simpler count the black pixels

or even simpler and faster, take middle line and count how often it switches from white to black

Upvotes: 0

Emond
Emond

Reputation: 50682

For the MCQ answers sheet, it might be easier to go by positions of the circles.

Just compare stock images of the clear, circled A, B, C and D's to the scanned images and see which differ the most. A simple darkness summation might be enough.

Also: Comparing the circles against each other might be useful too to compensate for a bad/dark/light scan or smudgy paper.

For special cases if the test isn't absolutely sure I'd probably pass it to a human being for further investigation. E.g., when you allow students to undo an answer by circling their second guess or when a student decides to make a real mess by using a bad eraser.

Final tip: make sure you do not accept answers that have the correct circle filled; make sure the other circles are clear at the same time so students can't cheat by filling all circles. (Some professors use a paper mask that overlays all bad answers so they can quickly spot unmarked correct answers. But if the student just marks all answers this fails big time.)

Upvotes: 3

Pantelis Natsiavas
Pantelis Natsiavas

Reputation: 5369

I would not know any "formal" algorithm matching your criteria. I would also doubt that you would find any.

When you say the circles are "darkened", this can be interpreted as this: "Many pixels (above a population threshold) would be black, or at least dark (above a colour threshold).". Based on known circle and radius, I would follow this approach (written in pseudocode but I suppose you get the meaning):

//define thresholds
colourThreshold=...
populationThreshold=...

centerPoint = getCircleCenter();
radius = getCircleRadius();
darkPixelsCount = 0;

for(x=centerPoint.X-radius;x<centerPoint.X+radius;x++){
   for(y=centerPoint.Y-sqrt(abs(radius^2-(x - centerPoint.X)^2));centerPoint.Y+sqrt(abs(radius^2-(x - centerPoint.X)^2));y++){

      if (image(x, y) >  colourThreshold){
         darkPixelsCounter++;      

         if(darkPixelsCounter > populationThreshold){
             //If you reach this point, circle has been darkened
             return;
         }

      }
    }
}

//If you reach this point, circle has not been darkened
return;

I don't know if it is efficient, or if there is a more elegant way to do it. I suppose you could play with performance and accuracy by moderating the thresholds.

Hope I helped!

Upvotes: 2

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