Hierarchical categorization tree based on a combined unsupervised-supervised classification

K-nearest neighbor (KNN) classification is an instance-based learning algorithm that has shown to be very effective when classifying images described by local features. In this paper, we present a combined unsupervised and supervised classification tree based on local descriptors and the KNN algorithm. The proposed tree outperforms the classification accuracy of the exact KNN algorithm.