Efficient object recognition using corner features

This paper presents a novel method for recognizing objects using corner features. As one of the most important local features, corner contains lots of information with the shape of the objects. Our approach detects corner points from images and describes the objects based on them. The features are highly distinctive, in the sense that a single feature can be correctly matched with high probability against a large database of features from many images. The recognition proceeds by matching individual features to a database of features from known objects using a fast nearest-neighbor algorithm. The performance on the obtained experimental results demonstrates that the proposed method is efficient.