A Review on SIFT and SURF for Underwater Image Feature Detection and Matching

Fast and robust image recognition and matching is an important task in the underwater domain. Autonomous Underwater Vehicles (AUV) use images for detecting and recognising object or scene of interest. Interest points are extracted from images that are captured by the cameraon the AUV. In this paper, feature detectors SIFT and SURF are investigated as applicable to the underwater environment. They are reviewed and compared in terms of robustness, accuracy, and speed with the aim of identifying a method which is computationally-efficient in finding good corresponding points between two underwater images.