Multi-annulus partition based image representation for image classification

The paper proposes a new spatial extension of Bag-of-Features (BoF) formalism for classification tasks. The scheme is based on multi-annulus partition which contains much spatial information of image space. Experiments are conducted using final super-vector image representation in Support Vector Machine (SVM) framework for classification on Oxford flowers and 15 scenes data sets. The results of experiment have shown the effectiveness of our scheme in terms of multiple performance metrics. In addition, our scheme is conceptually simple and easily adoptable. It can lead to much more compact representations and more invariance to image transformation compared to several existing works.