Independent feature processing in the visual system

Summary A recognition experiment with a set of simple visual patterns was performed. The patterns were composed of three binary features: Lines, angles and curve segments. The pattern sets differed with respect to the distance between components and the symmetry of the arrangement. The empirical confusion matrices were analysed assuming two different models: A model assuming independent feature analysis and a model that assumes that one of the features is analysed independently of the other two. The main result was that quite a large distance between features was necessary to achieve independent processing of the features. Moreover, in the asymmetric pattern set the predictions of the independence model were better than in the symmetric pattern set.