Take the 2-minute tour ×
Signal Processing Stack Exchange is a question and answer site for practitioners of the art and science of signal, image and video processing. It's 100% free, no registration required.

What distance metric can I use for comparing image features like elongation and solidity of a contour of each image? Except Least Square and without using a support vector machine because i do not know at which class images belong.

share|improve this question
    
Have you tried using the first two eigenvectors of the contour matrix (or its covariance matrix) as a measure for elongation? –  Junuxx Feb 27 '13 at 9:59
add comment

1 Answer 1

up vote 3 down vote accepted

If I understood you correctly, each contour is described by a 2-element feature vector $f = [e, s]$, where $e$ is elongation and $s$ is solidity.

In that case, you might want to try the Mahalanobis distance, which is defined as follows: $$d(f_1, f_2) = \sqrt{(f_2 - f_1)C^{-1}(f_2 - f_1)}$$ where $f_1$ and $f_2$ are the feature vectors that you are comparing, and $C$ is the covariance matrix of your data set.

share|improve this answer
add comment

Your Answer

 
discard

By posting your answer, you agree to the privacy policy and terms of service.

Not the answer you're looking for? Browse other questions tagged or ask your own question.