By the way, your ground truth is the values you used when drawing the ellipse, not the values you detect with a different detection method. On Thu, Mar 5, 2015 at 10:07 AM, Kevin Keraudren < kevin.keraudren@googlemail.com> wrote:

Hi Arno, In order to stay on the safe side, why don't you post your actual code, with a test case highlighting the error you measure between the true centre of the ellipse and the detected one? Kind regards, Kevin

On Thu, Mar 5, 2015 at 9:53 AM, Arno Dietz <arnodietz86@googlemail.com> wrote:

...

Thank you very much Kevin and Johannes.

I see the rounding Problem, but it is just for the ellipse drawing. In my actual code I just use the Ellipse center like best [1] and best[2] without rounding. This still produces much more inaccurate ellipse center results than other methods like center of mass for example, althoug <http://www.dict.cc/englisch-deutsch/although.html>h I also use the anti-aliased input image. So is there any possibility to get more accurate results from the hough ellipse fit approach? If not, this is also ok, I just want to be on the safe side that it's not my fault. In that case I will have a look at the suggested approach from Johannes.

Am Donnerstag, 5. März 2015 01:21:48 UTC+1 schrieb Kevin Keraudren:

...

Hi Arno,

The first source of inaccuracy comes from your code, you need to round the values instead of truncating them:

#yc = int(best[1])

#xc = int(best[2])

#a = int(best[3])

#b = int(best[4])

yc = int(round(best[1]))

xc = int(round(best[2]))

a = int(round(best[3]))

b = int(round(best[4]))

See resulting image attached.

Kind regards,

Kevin

A second source of inaccuracy comes from your input ellipse: it is not a perfect ellipse because you drew it using anti-aliasing.

Third, you could fit an ellipse using RANSAC. How does this approach work

...

for you: http://stackoverflow.com/questions/28281742/fitting-a- circle-to-a-binary-image/28289147#28289147

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