The various results obtained by me as results of applying
the circle detection routine is shown below.
The detected circles are marked in red.
First, I demonstrate the circle detecttion capabilities
of the Hough transform
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Accumulator Maxima 114 |
Accumulator Threshold 100 |
Next, I demonstrate the Hough transform's capbility
of detecting circles amongst other shapes.
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Accumulator Maxima 112 |
Accumulator Threshold 95 |
Next, I demonstrate the Hough transform's capability
of detecting circles in noisy images.
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Accumulator Maxima 90 |
Accumulator Threshold 50 |
Now, I demonstrate the Hough Transform's cpability
on a real life image. The image is of the set of coins on a denim texture
background.
The Hough transform is used to detect a the larger
coins.
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Accumulator Maxima 42 (after gradient) |
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Gradient Threshold 0.8 |
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Other Experiments possible :
1. The accumulator resolution and
quantization can both be varied and the results studied.
2. Each edge point can be made
to vote for a neighbourhood of cells in the accumulator insted of just
on cell and the effect studied.
Salient Features of this Implementation :
1. Highly efficient due to use of Mid - point circle drawing Algorithm.
2. Very Interactive - allows the user to vary a lot
of parameters at runtime such as -
a) The choice of calculating the
Gradient Image
b) The Gradient Threshold
c) The Accumulator Threshold (The
routine reports the accumulator Maxima for easy selection of this threshold).
Page last updated on 28 January, 2004. | AT cse.iitd.ac.in | © Parag Chaudhuri , 2009 |