New binary descriptors based on BRISK sampling pattern for image retrieval

Over the last decade, feature point descriptors such as SIFT have become indispensable tools in the computer vision community. But, the descriptor´s high computational overhead becomes a significant concern when it has to be on a device with limited computational and storage resources. In order to make descriptors faster to compute and more compact, several binary descriptors such as ORB and BRISK have been proposed. These binary descriptors are not successful in image retrieval, so we propose new binary descriptors to increase the accuracy while maintaining computational efficiency.