Efficient near-duplicate image detection with created feature subset

The creation of distinctive subset of the interest points for near-duplicate image detection is significant in two terms. The former is that the query time decreases reasonably. The latter is that using the distinctive subset of the interest points for near-duplicate detection performs better than the ordinary subsets. In this paper, we propose a novel interest point selection method. Such a method, the distinctive subset is created with a density map which is calculated from the interest points to rank them. We examined some experiments to show the performance of the proposed method and we get a performance of 95.46% recall while the precision is 96.04%.