Why do number of features are different for same person's retinal image
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I am doing a project "Personal Identification on the basis of Retina". I have made feature matrix that comprise of distance and angles between a candidate a feature point and its 4 nearest neighbors. In my data set I have two images per person. When I calculate my feature matrix then for both the images of same person the number of extracted features is different. Will this difference effect the results in matching step between test data and training data?? Or there is some way through which I can correct this? Below are two images of same person.
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Image Analyst
2017-4-7
It depends on what you call a feature. For a simple example, let's say that your features were the optic disc diameter, and the number of vessel bifurcations. So that's just two features and it will be two features for all possible images, even though the values of those features may be different.
Or lets say the features were the optic disc diameter, the number of vessel bifurcations, and the (x,y) locations of vessel bifurcations. If you consider the list of locations as a single feature, since they can be stored in an N by 2 array, then you just have 3 features. However if you consider the list to be N features, then you have N+2 features total and that will vary from image to image because the number of bifurcations, N, will vary from image to image.
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